all_papers.md

Updated on: 231122 115706

• 3d/
  • A Closed-Form Solution to Single Underwater Camera Calibration Using Triple Wavelength Dispersion and Its Application to Single Camera 3D Reconstruction tip1709.pdf
  • Mesh R-CNN 1906.02739 iccv19.pdf
  • Sparse-to-Dense Depth Prediction from Sparse Depth Samples and a Single Image 1709.07492 icra18.pdf
• active_learning/
  • Active Learning Literature Survey.pdf
• alignment/
  • A Robust Method for Mosaicking Sequence Images Obtained from UAV icies10.pdf
  • Face Alignment Across Large Poses A 3D Solution CVPR2016.pdf
  • Large-pose Face Alignment via CNN-based Dense 3D Model Fitting CVPR2016.pdf
  • PoseNet A Convolutional Network for Real-Time 6-DOF Camera Relocalization iccv15.pdf
• annotation/
  • Automatic generation of ground truth for the evaluation of obstacle detection and tracking techniques 1807.05722.pdf
  • ByLabel A Boundary Based Semi-Automatic Image Annotation Tool wacv18.pdf
  • Deep Interactive Object Selection ax1603.pdf
  • Efficiently scaling up crowdsourced video annotation ijcv13.pdf
  • Human-Assisted Motion Annotation cvpr08.pdf
• autoencoder/
  • Masked Autoencoders Are Scalable Vision Learners 2111.06377.pdf
  • binary/
    • Learning deep compact descriptor with bagging auto-encoders for object retrieval icip15.pdf
    • Learning to Hash with Binary Deep Neural Network ax1607.05140 eccv16.pdf
    • Optimal Binary Autoencoding with Pairwise Correlations iclr17.pdf
  • denoising/
    • On denoising autoencoders trained to minimise binary cross-entropy ax1708.08487.pdf
    • Stacked Denoising Autoencoders 10.pdf
  • misc/
    • Reducing the Dimensionality of Data with Neural Networks science0607.pdf
    • Transforming auto-encoders icann11.pdf
  • notes/
    • beta-VAE Learning Basic Visual Concepts with a Constrained Variational Framework iclr17.pdf
    • Disentangling by Factorising ax1806.pdf
  • sparse/
    • A Hierarchical Approach for Handwritten Digit Recognition Using Sparse Autoencoder sl_14.pdf
    • Embarrassingly Shallow Autoencoders for Sparse Data ax1905.03375.pdf
    • Hashing with binary autoencoders ax1501.00756.pdf
    • Stacked sparse autoencoder and history of binary motion image for human activity recognition sp_mta19.pdf
    • Training Autoencoders in Sparse Domain aaai17.pdf
  • variational/
    • Auto-Encoding Variational Bayes ax1405.pdf
    • beta-VAE Learning Basic Visual Concepts with a Constrained Variational Framework iclr17.pdf
    • Complementary Set Variational Autoencoder for Supervised Anomaly Detection icassp18.pdf
    • Deep Convolutional Inverse Graphics Network ax1506 nis15.pdf
    • Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders rejected_iclr17.pdf
    • Disentangling by Factorising ax1806.pdf
    • Tutorial on Variational Autoencoders ax1606.05908.pdf
    • Understanding disentangling in beta-VAE nipsw17.pdf
    • Unsupervised Lesion Detection via Image Restoration with a Normative Prior ax181123.pdf
• bayesian/
  • A practical Bayesian framework for backpropagation networks. nc92.pdf
  • Bayesian Learning for Neural Networks thesis_book95.pdf
  • Bayesian methods for adaptive models thesis_caltech92.pdf
  • Keeping the neural net- works simple by minimizing the description length of the weights colt93.pdf
  • Variational Inference A Review for Statisticians ax1712.pdf
  • Variational Inference A Review for Statisticians ax1712_2.pdf
• bio_inspired/
  • A Bio-Inspired Robot with Visual Perception of Affordances eccv14.pdf
  • Human-level concept learning through probabilistic program induction.pdf
  • Lessons from the Primate Visual System eccv12.pdf
  • Visual parsing after recovery from blindness ps09.pdf
• class separability/
  • A note on the separability index 0812.1107.pdf
  • Data Separability for Neural Network Classifiers and the Development of a Separability Index 2005.13120.pdf
  • Separability Index in Supervised Learning.pdf
  • KS Test/
    • Critical_KS.pdf
    • kstest.pdf
    • SBL701_KS_test_Tables.pdf
• classification/
  • Accurate and Efficient Image Classification by Exploiting Sparsity Homa_Candidacy.pdf
  • Anytime recognition of objects and scenes cvpr14.pdf
  • ImageNet Classification with Deep Convolutional Neural Networks nips12.pdf
  • ImageNet classification with deep convolutional neural networks acm17.pdf
  • Imagenet classification with deep convolutional neural networks nips12.pdf
  • MACH Embarrassingly parallel K-class classification.pdf
  • Multi-Scale Dense Networks for Resource Efficient Image Classification ax1711.pdf
  • Place Recognition with ConvNet Landmarks Viewpoint-Robust, Condition-Robust, Training-Free rss15.pdf
  • Selective Search for Object Recognition IJCV2013.pdf
  • Very Deep Convolutional Networks for Large-Scale Image Recognition iclr15 1409.1556.pdf
  • Visual object-action recognition Inferring object affordances from human demonstration cviu_11.pdf
  • activity/
    • Continuous Learning of Human Activity Models Using Deep Nets eccv14.pdf
  • animal/
    • Learning to Recognize Animals by Watching Documentaries Using Subtitles as Weak Supervision 17.pdf
  • cell_classification/
    • 10.1007_978-3-319-46976-8.pdf
    • A deep convolutional neural network for classification of red blood cells in sickle cell anemia plos_cb_1710.pdf
    • A Deep Residual Inception Network for HEp-2 Cell Classification SL_dlmia17.pdf
    • Cells classification with deep learning siu17.pdf
    • Cross-Modal Transfer Learning for HEp-2 Cell Classification Based on Deep Residual Network ism17.pdf
    • Deep convolutional neural network based HEp-2 cell classification icpr1612.pdf
    • Deep Learning in Label-free Cell Classification nature_srep21471 1603.pdf
    • Deep Learning of Cell Classification Using Microscope Images of Intracellular Microtubule Networks icmla1712.pdf
    • DeepPap Deep Convolutional Networks for Cervical Cell Classification jbhi1711.pdf
    • DTFD-MIL Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification cvpr22.pdf
    • Evaluation of Morphological Features for Breast Cells Classification Using Neural Networks SL_taai.pdf
    • HEp-2 cell classification based on a Deep Autoencoding-Classification convolutional neural network isbi17.pdf
    • HEp-2 cell classification using a deep neural network trained for natural image classification siu16.pdf
    • HEp-2 Cell Classification Using K-Support Spatial Pooling in Deep CNNs SL_dlmia1609.pdf
    • HEp-2 Cell Image Classification With Deep Convolutional Neural Networks jbhi1703.pdf
    • HEp-2 specimen classification via deep CNNs and pattern histogram icpr1612.pdf
  • efficient/
    • Learning Efficient Convolutional Networks Through Network Slimming iccv17.pdf
  • evolution/
    • Large-Scale Evolution of Image Classifiers ax1706 icml17.pdf
    • Regularized Evolution for Image Classifier Architecture Search ax190216 aaai19.pdf
  • pipe_defect/
    • Automated defect classification in sewer closed circuit television inspections using deep convolutional neural networks AiC1807_SD.pdf
    • Automated detection of sewer pipe defects in closed-circuit television images using deep learning techniques AiC1811_SD.pdf
    • Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types 171128 Computer-Aided_Civil_and_Infrastructure_Engineering.pdf
    • CLASSIFICATION OF UNDERWATER PIPELINE EVENTS USING DEEP CONVOLUTIONAL NEURAL NETWORKS icassp17_poster.pdf
    • Deep learning-based damage detection for sewer pipe inspection using faster R-CNN 180414_Full_Paper_ICCCBE2018.pdf
    • Development and Improvement of Deep Learning Based Automated Defect Detection for Sewer Pipe Inspection Using Faster R-CNN ACSE18_springer.pdf
    • Sewer damage detection from imbalanced CCTV inspection data using deep convolutional neural networks with hierarchical classification AiC1905_SD.pdf
    • Small Defect Detection Using Convolutional Neural Network Features and Random Forests eccvw18.pdf
    • Visual Inspection of Storm-Water Pipe Systems using Deep Convolutional Neural Networks ICINCO_2018_67_CR.pdf
    • misc/
      • A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure AEI15_SD.pdf
      • Vision-based Structural Inspection using Multiscale Deep Convolutional Neural Networks ax1805.01055.pdf
  • svm/
    • A tutorial on support vector machines for pattern recognition.pdf
    • SVM.pdf
    • svm15.pdf
  • thermal_imaging/
    • Deep Thermal Imaging Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns ax1803.pdf
  • video/
    • Beyond Short Snippets Deep Networks for Video Classification cvpr15.pdf
    • Deep Learning from Temporal Coherence in Video icml09.pdf
    • Learning Spatiotemporal Features with 3D Convolutional Networks iccv15.pdf
    • Long-term Recurrent Convolutional Networks for Visual Recognition and Description ax1411.4389 cvpr15.pdf
• compressed_sensing/
  • A deep learning approach to compressive sensing with convolutional autoencoders.pdf
  • A Deep Learning Approach to Structured Signal Recovery ax1508.04065.pdf
  • Compressed sensing IT_April06.pdf
  • Deep Learning Sparse Ternary Projections for Compressed Sensing of Images 1708.08311 GlobalSIP17.pdf
  • Output Encoding by Compressed Sensing for Cell Detection with Deep Convnet aaai20.pdf
  • Perceptual Compressive Sensing ax1802.00176 prcv18.pdf
  • compressed_input/
    • Compressed Sensing using Generative Models ax1703.03208.pdf
    • ConvCSNet A Convolutional Compressive Sensing Framework Based on Deep Learning ax1801.10342.pdf
    • ISTA-Net Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing_cvpr18.pdf
    • LAPRAN A Scalable Laplacian Pyramid Reconstructive Adversarial Network for Flexible Compressive Sensing Reconstruction ax1807.09388 eccv18.pdf
    • Learning to invert Signal recovery via Deep Convolutional Networks ax1701.03891.pdf
    • Multi-Scale Deep Compressive Sensing Network ax1809.05717 vcip.pdf
    • ReconNet Non-Iterative Reconstruction of Images from Compressively Sensed Measurements_CVPR_2016.pdf
  • MRI/
    • DAGAN Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction tmi18.pdf
    • Deep residual learning for compressed sensing MRI isbi17.pdf
    • Learning a Variational Network for Reconstruction of Accelerated MRI Data ax1704.00447.pdf
  • review/
    • A Review of Sparse Recovery Algorithms 1812.pdf
    • A survey of sparse representation algorithms and applications ax16.pdf
    • A Systematic Review of Compressive Sensing Concepts, Implementations and Applications access18.pdf
    • Algorithms for First-order Sparse Reinforcement Learning phd16.pdf
    • An Overview on Algorithms for Sparse Recovery.pdf
    • Compressive Sensing Performance Comparison Of Sparse Recovery Algorithms ax1801.09744.pdf
    • Greedy Algorithms for Sparse Reinforcement Learning icml2012.pdf
    • Learning Fast Approximations of Sparse Coding icml10.pdf
    • Learning Sparse Representations in Reinforcement Learning with Sparse Coding ax1707.pdf
    • Learning Sparse Representations in Reinforcement Learning with Sparse Coding ijcai17.pdf
    • Sparse Multi-Task Reinforcement Learning.pdf
    • Sparse Recovery Using Sparse Matrices.pdf
    • Tutorial Sparse Recovery Using Sparse Matrices.pdf
  • sparse_coding/
  • sparse_input/
    • BCS Compressive Sensing for Binary Sparse Signals.pdf
  • video/
    • CSVideoNet A Real-time End-to-end Learning Framework for High-frame-rate Video Compressive Sensing ax1612.05203 wacv18.pdf
    • Deep Fully-Connected Networks for Video Compressive Sensing ax1603.04930v2 els_dsp18.pdf
• curve_revovery/
  • A Robust Rigid Skeleton Extraction Method from Noisy Visual Hull Model ijars15.pdf
  • Analytic Curve Detection from a Noisy Binary Edge Map using Genetic Algorithm.pdf
• datasets/
  • 1 year, 1000 km The Oxford RobotCar dataset ijrr16_11.pdf
  • 80 Million Tiny Images A Large Data Set for Nonparametric Object and Scene Recognition pami08.pdf
  • A benchmark for comparison of cell tracking algorithms bioinformatics14.pdf
  • A Public Video Dataset for Road Transportation Applications (2013) .pdf
  • Beyond Standard Benchmarks Parameterizing Performance Evaluation in Visual Object Tracking_iccv17.pdf
  • Cats and Dogs cvpr12.pdf
  • Data Engineering for Everyone 2102.11447.pdf
  • Microsoft COCO Common Objects in Context ax1502 eccv14.pdf
  • Objectnet A large-scale bias-controlled dataset for pushing the limits of object recognition models nips19.pdf
  • Semantic Understanding of Scenes through ADE20K Dataset ax1608.05442 cvpr17 ijcv19.pdf
  • Semantic Understanding of Scenes through the ADE20K Dataset ax1608.05442.pdf
  • Sim4CV A Photo-Realistic Simulator for Computer Vision Applications ijcv18.pdf
  • The Unmanned Aerial Vehicle Benchmark Object Detection and Tracking_eccv18.pdf
  • Training a Convolutional Neural Network for Multi-Class Object Detection Using Solely Virtual World Data icavss16_8.pdf
  • Vehicle Tracking by Simultaneous Detection and Viewpoint Estimation iwinac13.pdf
  • agro/
    • Perception Datasets for Anomaly Detection in Autonomous Driving A Survey 2302.02790.pdf
  • animal/
    • The iNaturalist Species Classification and Detection Dataset ax1804.pdf
    • The INaturalist Species Classification and Detection Dataset_cvpr18-supp.pdf
    • The INaturalist Species Classification and Detection Dataset_cvpr18.pdf
  • detection/
    • DOTA A Large-Scale Dataset for Object Detection in Aerial Images_cvpr18.pdf
    • Performance Evaluation of Object Detection and Tracking in Video TR2006-041.pdf
    • Performance Evaluation of Object Detection and Tracking in Video.pdf
    • Performance measures for object detection evaluation prl10_7.pdf
    • The PASCAL Visual Object Classes (VOC) Challenge ijcv_voc09.pdf
  • multi_object_tracking/
    • CityFlow A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification 1903.09254 cvpr19.pdf
    • Fully Automatic, Real-Time Vehicle Tracking for Surveillance Video crv17.pdf
    • MOT16 A Benchmark for Multi-Object Tracking ax16_5.pdf
    • MOTChallenge 2015 Towards a Benchmark for Multi-Target Tracking ax15_8.pdf
    • PathTrack Fast Trajectory Annotation with Path Supervision iccv17 supplementary.pdf
    • PathTrack Fast Trajectory Annotation with Path Supervision iccv17.pdf
    • TAO A Large-Scale Benchmark for Tracking Any Object 2005.10356 eccv20.pdf
    • The Unmanned Aerial Vehicle Benchmark Object Detection and Tracking ax1804.00518 eccv18.pdf
    • Tracking and Detection Challenge How crowded can it get 1906.04567 cvpr19.pdf
    • Training a Convolutional Neural Network for Multi-Class Object Detection Using Solely Virtual World Data avss16.pdf
    • Virtual Worlds as Proxy for Multi-Object Tracking Analysis 1605.06457 cvpr16.pdf
    • WILDTRACK A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection_cvpr18.pdf
    • cell tracking/
      • A benchmark for comparison of cell tracking algorithms bio_informatics14.pdf
      • An objective comparison of cell-tracking algorithms nature methods 17.pdf
      • Cell Tracking with Mitosis Detection Dataset Challenge_CVPRW20.pdf
    • uav/
      • Vision Meets Drones Past, Present and Future 2001.06303v2.pdf
  • perception/
    • Argoverse 2 Next Generation Datasets for Self-Driving Perception and Forecasting nips23.pdf
    • Argoverse 3D Tracking and Forecasting with Rich Maps cvpr19.pdf
    • Lyft One Thousand and One Hours Self-driving Motion Prediction Dataset houston21a.pdf
    • nuScenes A multimodal dataset for autonomous driving cvpr20.pdf
    • OpenOccupancy A Large Scale Benchmark for Surrounding Semantic Occupancy Perception iccv23.pdf
    • Scalability in Perception for Autonomous Driving Waymo Open Dataset CVPR20.pdf
    • TractorEYE Vision-based Real-time Detection for Autonomous Vehicles in Agriculture phd thesis 2017.pdf
    • planning/
      • Large scale interactive motion forecasting for autonomous driving The waymo open motion dataset iccv21.pdf
      • SHIFTS 2.0 EXTENDING THE DATASET OF REAL DISTRIBUTIONAL SHIFTS.pdf
    • rgbd/
      • SceneNN a Scene Meshes Dataset with aNNotations_3dv16.pdf
  • segmentation/
    • A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation cvpr16.pdf
    • The SYNTHIA Dataset A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes cvpr16.pdf
  • single_object_tracking/
    • CDTB A Color and Depth Visual Object Tracking Dataset and Benchmark iccv19.pdf
    • LaSOT A High-quality Benchmark for Large-scale Single Object Tracking ax1809.07845.pdf
    • LaSOT A High-quality Benchmark for Large-scale Single Object Tracking ax190327 cvpr19.pdf
    • Long-term Tracking in the Wild A Benchmark ax180810_eccv18.pdf
    • Need for Speed A Benchmark for Higher Frame Rate Object Tracking_iccv17.pdf
    • TrackingNet A Large-Scale Dataset and Benchmark for Object Tracking in the Wild ax1803.10794 eccv18.pdf
    • TrackingNet A Large-Scale Dataset and Benchmark for Object Tracking in the Wild_eccv18.pdf
    • UAV123 A Benchmark and Simulator for UAV Tracking eccv16 supp.pdf
    • UAV123 A Benchmark and Simulator for UAV Tracking eccv16.pdf
  • video_captioning/
    • ActivityNet A Large-Scale Video Benchmark for Human Activity Understanding cvpr15.pdf
    • Neural Script Knowledge through Vision and Language and Sound cvpr22.pdf
    • Towards automatic learning of procedures from web instructional videos aaai18 1703.09788.pdf
    • Visual genome Connecting language 1602.07332 ijcv17.pdf
  • video_detection/
    • YouTube-BoundingBoxes A Large High-Precision Human-Annotated Data Set for Object Detection in Video ax170324.pdf
• deblurring/
  • Blind Image Deblurring Using Dark Channel Prior cvpr16.pdf
  • DeblurGAN Blind Motion Deblurring Using Conditional Adversarial Networks ax1804_cvpr18.pdf
  • DeblurGAN Blind Motion Deblurring Using Conditional Adversarial Networks cvpr18.pdf
  • Deblurring Images via Dark Channel Prior tpami1709.pdf
  • Image Deblurring via Extreme Channels Prior cvpr17.pdf
• deep_learning/
  • Adaptable Hamiltonian neural networks 2102.13235.pdf
  • Differentiable Patch Selection for Image Recognition 2104.03059 cvpr21.pdf
  • DiffusionNet Accelerating the solution of Time-Dependent partial differential equations using deep learning 2011.10015v1.pdf
  • Federated Quantum Machine Learning 2103.12010.pdf
  • Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains nips20 2006.10739.pdf
  • Group Equivariant Convolutional Networks 1602.07576 icml16.pdf
  • Neural message passing for quantum chemistry 1704.01212.pdf
  • Non-local Neural Networks 1711.07971 cvpr18.pdf
  • Siamese Neural Networks for One-shot Image Recognition.pdf
  • adversarial/
    • The Elephant in the Room 1808.03305.pdf
  • atrous/
    • Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks icip13 ax1302.1700.pdf
    • Multi-Scale Context Aggregation by Dilated Convolutions iclr16 ax1511.07122.pdf
  • augmentation/
    • Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation 2012.07177.pdf
  • batch_normalization/
    • Batch Normalization Accelerating Deep Network Training by Reducing Internal Covariate Shift ax1503.pdf
  • biological/
    • Towards an integration of deep learning and neuroscience ax1606.03813.pdf
    • Towards Biologically Plausible Deep Learning ax1502.04156.pdf
  • class_imbalance/
    • A Review on Ensembles for the Class Imbalance Problem Bagging-, Boosting-, and Hybrid-Based Approaches TSMC1108.pdf
    • A Survey of Predictive Modelling under Imbalanced Distributions 1505.01658.pdf
    • A survey on addressing high-class imbalance in big data jbd_sl1811.pdf
    • Class Imbalance Problem in Data Mining Review 1305.1707.pdf
    • Classification with class imbalance problem A review jsoco1511.pdf
    • Learning from imbalanced data open challenges and future directions pAI_sl1604.pdf
    • Learning from Imbalanced Data tkde0906.pdf
    • On the combined effect of class imbalance and concept complexity in deep learning 2107.14194.pdf
    • Survey on deep learning with class imbalance jbd_sl1903.pdf
    • Training Deep Neural Networks on Imbalanced Data Sets IJCNN15l.pdf
  • compression/
    • A Gift from Knowledge Distillation Fast Optimization, Network Minimization and Transfer Learning CVPR17.pdf
    • Compression of Deep Neural Networks by combining pruning and low rank decomposition nips18.pdf
    • Domain-adaptive deep network compression ax1709.01041.pdf
    • Domain-Adaptive Deep Network Compression iccv17.pdf
    • FitNets Hints for Thin Deep Nets ax1505.pdf
    • Learning Efficient Convolutional Networks through Network Slimming ax1708.06519 iccv17.pdf
    • Paying More Attention to Attention Improving the Performance of Convolutional Neural Networks via Attention Transfer ax1702.pdf
    • Pelee A Real-Time Object Detection System on Mobile Devices ax190118.pdf
    • Pruning Convolutional Neural Networks for Resource Efficient Inference ax1707.pdf
    • Pruning Filters for Efficient ConvNets ax1608.08710.pdf
    • ThiNet A Filter Level Pruning Method for Deep Neural Network Compression ICCV17.pdf
  • curriculum/
    • A Survey on Curriculum Learning 2010.13166 tpami21.pdf
  • deformable/
    • Deformable Convolutional Networks 1703.06211 iccv17.pdf
  • densenet/
    • CondenseNet An Efficient DenseNet using Learned Group Convolutions ax1806.pdf
    • Densely Connected Convolutional Networks ax1801 cvpr17.pdf
  • distillation/
    • Mean teachers are better role models Weight-averaged consistency targets improve semi-supervised deep learning results 1703.01780.pdf
  • domain_adaptation/
    • Deep visual domain adaptation A survey neurocomputing1810_sd.pdf
    • DINE Domain Adaptation from Single and Multiple Black-box Predictors cvpr22.pdf
    • Invariant Risk Minimization 1907.02893.pdf
    • Unsupervised Domain Adaptation by Backpropagation icml15.pdf
  • dropout/
    • Dropout A Simple Way to Prevent Neural Networks from Overfitting jmlr14.pdf
    • Dropout as a Bayesian Approximation Appendix ax1605.pdf
    • Dropout as a Bayesian Approximation Representing Model Uncertainty in Deep Learning ax1610.pdf
    • Improving neural networks by preventing co-adaptation of feature detectors ax1207.pdf
    • Uncertainty in Deep Learning (PhD Thesis) cambridge1705.pdf
  • efficient/
    • Abandoning the Dark Arts Scientific Approaches to Efficient Deep. Learning nipsw19.pdf
    • An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection AX1904.09730 CVPRW19.pdf
    • Be Your Own Teacher Improve the Performance of Convolutional Neural Networks via Self Distillation ax1905.08094 iccv19.pdf
    • EfficientNet_Rethinking model scaling for CNNs.pdf
    • MobileNets Efficient Convolutional Neural Networks for Mobile Vision Applications ax1704.04861.pdf
    • MobileNetV2 inax Inverted Residuals and Linear Bottlenecks 1801.04381.pdf
    • Searching for MobileNetV3 ax1905.02244.pdf
  • ensemble/
    • Distilling the Knowledge in a Neural Network ax1503.02531.pdf
  • fourier/
    • Fast Fourier Transformation for Optimizing Convolutional Neural Networks in Object Recognition 2010.04257v1.pdf
    • Fourier Neural Operator for Parametric Partial Differential Equations 2010.08895v1.pdf
  • fully_convolutional/
    • Striving for Simplicity The All Convolutional Net ax1504 iclrw15.pdf
  • graph/
    • Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering nips18.pdf
    • Hierarchical graph neural nets can capture long-range interactions 2107.07432v1.pdf
    • Relational inductive biases, deep learning, and graph networks ax1810.pdf
    • Semi-Supervised Classification with Graph Convolutional Networks 1609.02907 iclr17.pdf
  • hardware/
    • 11 TeraFLOPs per second photonic convolutional accelerator for deep learning optical neural networks 2011.07393.pdf
    • ZeRO-Infinity Breaking the GPU Memory Wall for Extreme Scale Deep Learning 2104.07857 Microsoft.pdf
  • hybrid_hand_crafted/
    • Combining ConvNets with Hand-Crafted Features for Action Recognition Based on an HMM-SVM Classifier ax1602.00749.pdf
    • Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors. sensors-18-00699-v2.pdf
    • Combining deep learning and hand-crafted features for skin lesion classification ipta06.pdf
    • Evaluating the Utility of Hand-crafted Features in Sequence Labelling ax1808.pdf
    • Object Classification using Ensemble of Local and Deep Features ax1712.04926.pdf
    • Skin Lesion Classification Via Combining Deep Learning Features and Clinical Criteria Representations bax1808.pdf
    • The Impact of Replacing Complex Hand-Crafted Features with Standard Features for Melanoma Classification Using Both Hand-Crafted and Deep Features intellisys18_spr.pdf
  • hyper_parameters/
    • A disciplined approach to neural network hyper-parameters Part 1 -- learning rate, batch size, momentum, and weight decay ax1803.09820.pdf
    • Algorithms for Hyper-Parameter Optimization nips11.pdf
  • inception/
    • Convolution in Convolution for Network in Network tnnls1805.pdf
    • Deformable Convolutional Networks ax1706 iccv17.pdf
    • Going Deeper with Convolutions ax1409 cvpr15.pdf
    • Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning ax1608 aaai17.pdf
    • Network In Network ax1403.pdf
    • Rethinking the Inception Architecture for Computer Vision ax1512 cvpr16.pdf
    • Xception Deep Learning with Depthwise Separable Convolutions ax170404.pdf
  • large_models/
    • Designing Network Design Spaces 2003.13678 cvpr20 facebook.pdf
    • GPipe Efficient Training of Giant Neural Networks using Pipeline Parallelism 181212.pdf
    • Lingvo a Modular and Scalable Framework for Sequence-to-Sequence Modeling ax190221.pdf
  • libraries/
    • DoubleML -- An Object-Oriented Implementation of Double Machine Learning in Python 2104.03220.pdf
    • Einops Clear and Reliable Tensor Manipulations with Einstein-like Notation iclr22.pdf
    • Kornia an Open Source Differentiable Computer Vision Library for PyTorch 1910.02190.pdf
    • Technical Report on the CleverHans v2.1.0 Adversarial Examples Library 1610.00768.pdf
  • mixed_precision/
    • Mixed Precision Training ax1802 iclr18.pdf
  • nas/
    • Can weight sharing outperform random architecture search An investigation with TuNAS cvpr20.pdf
    • DARTS Differentiable Architecture Search ax180624.pdf
    • Efficient Neural Architecture Search with Network Morphism ax1806.pdf
    • Efficient Neural Architecture Search via Parameter Sharing ax1802.03268.pdf
    • Learning Transferable Architectures for Scalable Image Recognition ax1804.pdf
    • MnasNet Platform-Aware Neural Architecture Search for Mobile ax180731.pdf
    • Neural Architect A Multi-objective Neural Architecture Search with Performance Prediction.pdf
    • Neural Architecture Search A Survey.pdf
    • Neural Architecture Search with Reinforcement Learning ax170215.pdf
    • Progressive Neural Architecture Search ax1807 eccv18.pdf
    • Simple And Efficient Architecture Search for Convolutional Neural Networks ax1711.pdf
  • notes/
    • Decoupled Neural Interfaces using Synthetic Gradients ax1608.05343.pdf
    • Do Deep Nets Really Need to be Deep ax1410 nips14.pdf
    • EfficientNet_ Rethinking Model Scaling for Convolutional Neural Networks.pdf
    • Understanding Synthetic Gradients and Decoupled Neural Interfaces ax1703.00522.pdf
  • old/
    • Learning representations by back-propagating errors nature86.pdf
  • optimization/
    • Adam A Method for Stochastic Optimization ax17_1.pdf
    • Adaptive subgradient methods for online learning and stochastic optimization jmlr11.pdf
    • An overview of gradient descent optimization algorithms ax1609.04747.pdf
    • Backpropagation through time what it does and how to do it ieee90.pdf
    • Categorical Reparameterization with Gumbel-Softmax 1611.01144.pdf
    • Cockpit A Practical Debugging Tool for Training Deep Neural Networks 2102.06604.pdf
    • Deep Convolutional Neural Networks with Unitary Weights 2102.11855.pdf
    • Deep learning via Hessian-free optimization.pdf
    • Delving Deep into Rectifiers Surpassing Human-Level Performance on ImageNet Classification ax1502.01852.pdf
    • Don't Decay the Learning Rate, Increase the Batch Size iclr18.pdf
    • Gradients without Backpropagation 2202.08587.pdf
    • On the Variance of the Adaptive Learning Rate and Beyond ax1908.03265.pdf
    • You Only Train Once Loss-Conditional Training of Deep Networks iclr20.pdf
  • ordinal regression/
    • Ordinal Regression with Multiple Output CNN for Age Estimation cvpr16.pdf
  • perception/
    • Delving into the Devils of Bird's-eye-view Perception A Review, Evaluation and Recipe 2209.05324.pdf
    • Geometric-aware Pretraining for Vision-centric 3D Object Detection 2304.03105.pdf
    • OccFormer Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction iccv23 2304.05316.pdf
    • Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction cvpr23 2302.07817.pdf
  • regnet/
    • Designing Network Design Spaces 2003.13678v1.pdf
  • relation_net/
    • A simple neural network module for relational reasoning 1706.01427.pdf
  • resnet/
    • Aggregated Residual Transformations for Deep Neural Networks ax170411 cvpr17.pdf
    • Deep Residual Learning for Image Recognition ax1512.pdf
    • Identity Mappings in Deep Residual Networks ax1607_eccv16.pdf
    • Wider or Deeper Revisiting the ResNet Model for Visual Recognition ax1611.pdf
  • review/
    • A Survey of Inductive Biases for Factorial Representation-Learning ax1612.05299.pdf
    • Deep Learning for Computer Vision A Brief Review cin1802 hindawi.pdf
    • Deep Learning for Computer Vision A Brief Review cin_hindawi18.pdf
    • Deep Learning in Neural Networks An Overview.pdf
    • Deep learning nature1505.pdf
    • Learning deep architectures for AI tr09.pdf
    • On the opportunities and risks of foundation models ax2108..pdf
  • stereo_matching/
    • Efficient Deep Learning for Stereo Matching cvpr16.pdf
    • MatchNet Unifying feature and metric learning for patch-based matching cvpr15.pdf
    • Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches ax16_5.pdf
  • synthetic_gradients/
    • Decoupled Neural Interfaces using Synthetic Gradients ax1608.05343.pdf
    • Decoupled Parallel Backpropagation with Convergence Guarantee ax1804.10574.pdf
    • Deep supervised learning using local errors ax1711.06756.pdf
    • Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation ax1308.3432.pdf
    • Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets iclr19_review.pdf
    • Understanding Synthetic Gradients and Decoupled Neural Interfaces ax1703.00522.pdf
  • theory/
    • Building Machines That Learn and Think Like People ax1611.pdf
    • Counterfactual Explanations for Machine Learning A Review 2010.10596v1.pdf
    • Deep Learning and the Information Bottleneck Principle ax1503.02406 ite15.pdf
    • Do Deep Nets Really Need to be Deep ax1410 nips14.pdf
    • Do Wide and Deep Networks Learn the Same Things Uncovering How Neural Network Representations Vary with Width and Depth 2010.15327v1.pdf
    • How Neural Networks Extrapolate From Feedforward to Graph Neural Networks 2009.11848.pdf
    • Interpretable Machine Learning – A Brief History, State-of-the-Art and Challenges 2010.09337v1.pdf
    • Neural Tangent Kernel Convergence and generalization in neural networks nips18.pdf
    • On the Expressive Power of Deep Neural Networks ax1706.pdf
    • On the Number of Linear Regions of Deep Neural Networks ax1406 nips14.pdf
    • Opening the black box of Deep Neural Networks via Information ax1703.00810.pdf
    • Provable Benefits of Overparameterization in Model Compression From Double Descent to Pruning Neural Networks 2012.08749.pdf
    • Provable Bounds for Learning Some Deep Representations icml14.pdf
    • Sensitivity and Generalization in Neural Networks An Empirical Study iclr18.pdf
    • Shapley Explanation Networks 2104.02297 iclr21.pdf
    • Underspecification Presents Challenges for Credibility in Modern Machine Learning 2011.03395.pdf
    • Understanding Deep Neural Networks with Rectified Linear Units ax1707.pdf
    • Visualizing and understanding convolutional neural networks ECCV2014.pdf
    • #old/
      • Saliency maps and attention selection in scale and spatial coordinates an information theoretic approach iccv95.pdf
      • Understanding the difficulty of training deep feedforward neural networks icas10.pdf
    • adversarial/
      • Adversarial examples in the physical world ax1702.pdf
      • Boosting Adversarial Attacks with Momentum} ax1710.06081 cvpr18.pdf
      • DeepFool a simple and accurate method to fool deep neural networks 1511.04599.pdf
      • Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser ax1803.pdf
      • Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks ax1511.04508.pdf
      • Ensemble Adversarial Training Attacks and Defenses ax1807.pdf
      • Explaining and Harnessing Adversarial Examples ax1503.pdf
      • Intriguing properties of neural networks ax1312.6199.pdf
      • Practical Black-Box Attacks against Machine Learning ax1703.pdf
      • Towards Evaluating the Robustness of Neural Networks ax1703.pdf
    • explainable/
      • Evaluating Explainable Artificial Intelligence Methods for Multi-label Deep Learning Classification Tasks in Remote Sensing 2104.01375.pdf
      • Explainable AI current status and future directions 2107.07045v1.pdf
      • Explainable AI Interpreting, Explaining and Visualizing Deep Learning lncs19_sl.pdf
      • Grad-CAM Visual Explanations from Deep Networks via Gradient-based Localization ijcv19.pdf
  • transfer/
    • Big Transfer (BiT) General Visual Representation Learning ax2005.pdf
    • Bringing Impressionism to Life with Neural Style Transfer in Come Swim arxiv17.pdf
    • Domain Adaptive Neural Networks for Object Recognition ax1409.6041.pdf
    • How transferable are features in deep neural networks nips14.pdf
    • Transfer Learning handbook09.pdf
    • Unsupervised Image-to-Image Translation Networks ax180215.pdf
  • transformer/
    • An Image is Worth 16x16 Words Transformers for Image Recognition at Scale 2010.11929.pdf
    • Attention is All you Need nips17.pdf
    • Axial Attention in Multidimensional Transformers 1912.12180.pdf
    • Emerging Properties in Self-Supervised Vision Transformers 2104.14294 facebook.pdf
    • Exploring Self-attention for Image Recognition 2004.13621 cvpr20.pdf
    • On the relationship between self- attention and convolutional layers 1911.03584 iclr20.pdf
    • Pervasive Attention 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction 1808.03867 conll18.pdf
    • Quantifying Attention Flow in Transformers 2005.00928.pdf
    • Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning 2206.02647.pdf
    • Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples 2104.13963 facebook.pdf
    • Swin Transformer Hierarchical Vision Transformer using Shifted Windows 2103.14030.pdf
    • Transformer visualization via dictionary learning contextualized embedding as a linear superposition of transformer factors 2103.15949.pdf
    • #tutorials/
    • graph/
      • Relational Attention Generalizing Transformers for Graph-Structured Tasks iclr23.pdf
    • review/
      • An Introduction to Transformers 2304.10557.pdf
      • Transformers in Vision A Survey 2101.01169.pdf
    • video/
      • TimeSformer Is Space-Time Attention All You Need for Video Understanding icml21.pdf
      • Video Swin Transformer cvpr22.pdf
      • Vivit A video vision transformer iccv21.pdf
  • unsorted/
    • Adaptive deconvolutional networks for mid and high level feature learning iccv11.pdf
    • Convolutional neural networks on graphs with fast localized spectral filtering nips16.pdf
    • Deep Learning A Critical Appraisal ax1801.00631.pdf
    • Deep Networks with Stochastic Depth arxiv16.pdf
    • End-To-End Memory Networks nips15.pdf
    • Evaluating the Robustness of Neural Networks An Extreme Value Theory Approach ax180131 iclr18.pdf
    • Geometric deep learning going beyond Euclidean data ax1705.pdf
    • Learning Explanatory Rules from Noisy Data ax1711.04574.pdf
    • Neural GPUs Learn Algorithms iclr16.pdf
    • Neural Machine Translation by Jointly Learning to Align and Translate iclr15.pdf
    • Sequence to Sequence Learning with Neural Networks nips14.pdf
    • Squeeze-and-Excitation Networks ax1804 cvpr18.pdf
    • SqueezeNext Hardware-Aware Neural Network Design ax180827.pdf
    • Weight Uncertainty in Neural Networks ax1505 icml15.pdf
  • unsupervised/
    • Classifier Crafting Turn Your ConvNet into a Zero-Shot Learner! 2103.11112.pdf
    • Emerging Properties in Self-Supervised Vision Transformers 2104.14294.pdf
    • Self-supervised Pretraining of Visual Features in the Wild 2103.01988 facebook.pdf
    • Unsupervised Learning of Visual Features by Contrasting Cluster Assignments 2006.09882 nips20.pdf
    • motion_prediction/
      • Unsupervised Learning of Long-Term Motion Dynamics for Videos ax1704.pdf
    • notes/
      • Learning Features by Watching Objects Move ax170412 cvpr17.pdf
    • pixel_prediction/
      • Context Encoders Feature Learning by Inpainting ax1604.07379.pdf
    • review/
      • Representation Learning A Review and New Perspectives ax1404 tpami13.pdf
    • segmentation/
      • Learning Features by Watching Objects Move ax170412 cvpr17.pdf
    • time_series/
      • Deep Temporal Clustering Fully Unsupervised Learning of Time-Domain Features ax1802.01059.pdf
      • Unsupervised Feature Learning from Time Series ijcai.pdf
  • vgg/
    • Very Deep Convolutional Networks for Large-Scale Image Recognition ax1409.1556.pdf
  • weak_supervision/
    • Self-Training with Weak Supervision 2104.05514.pdf
• deep_reinforcement_learning/
  • A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking 2011.07537v1.pdf
  • Active Object Localization With Deep Reinforcement Learning iccv15.pdf
  • Asynchronous Methods for Deep Reinforcement Learning ax16_6.pdf
  • Benchmarking Deep Reinforcement Learning for Continuous Control icml16.pdf
  • Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments ax180223 iclr18.pdf
  • Continuous control with deep reinforcement learning iclr16 ax1602.pdf
  • Continuous Deep Q-Learning with Model-based Acceleration ax1603.pdf
  • DEEP REINFORCEMENT LEARNING AN OVERVIEW ax1709.pdf
  • Deep Reinforcement Learning An Overview ax17_1.pdf
  • Deep Reinforcement Learning that Matters ax1711.pdf
  • Deep Reinforcement Learning with Double Q-learning corr15 ax15_12.pdf
  • Deterministic Policy Gradient Algorithms icml14.pdf
  • Dueling Network Architectures for Deep Reinforcement Learning ax16_5.pdf
  • End-to-End Training of Deep Visuomotor Policies arxiv16_4.pdf
  • Human-level control through deep reinforcement learning nature1502.pdf
  • Imagination-Augmented Agents for Deep Reinforcement Learning ax180214.pdf
  • Kickstarting Deep Reinforcement Learning ax1803.03835.pdf
  • Mastering the game of Go with deep neural networks and tree search nature16_1.pdf
  • Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning ax1712.pdf
  • Playing Atari with Deep Reinforcement Learning nips13 ax13_9.pdf
  • Proximal Policy Optimization Algorithms ax1708.pdf
  • Rainbow Combining Improvements in Deep Reinforcement Learning ax1710.pdf
  • Reinforcement and Deep Reinforcement Machine Learning sl rhml17.pdf
  • Stable reinforcement learning with recurrent neural networks SL jcta11.pdf
  • Temporal Difference Models Model-Free Deep RL for Model-Based Control iclr18_ur.pdf
  • Training Larger Networks for Deep Reinforcement Learning 2102.07920.pdf
  • Trust Region Policy Optimization ax17_4.pdf
• denoising/
  • Patch-based video denoising with optical flow estimation tip16.pdf
  • Polyview Fusion A Strategy to Enhance Video-Denoising Algorithms tip12.pdf
• document_recognition/
  • A Meaningful Information Extraction System for Interactive Analysis of Documents icdar19.pdf
  • Attend, Copy, Parse End-to-end information extraction from documents icdar19.pdf
  • Graphical Object Detection in Document Images icdar19.pdf
  • Table Detection in Invoice Documents by Graph Neural Networks icdar19.pdf
• dynamic_programming/
  • Automatic differentiation in machine learning a survey ax1802.pdf
  • Demystifying Differentiable Programming ShiftReset the Penultimate Backpropagator 180327.pdf
  • Differentiable Programming for Image Processing and Deep Learning in Halide siggraph18.pdf
• event_camera/
  • Dynamic Vision Sensors for Human Activity Recognition ax1803.04667 acpr17.pdf
  • Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars ax1804.01310 cvpr18.pdf
  • PRED18 Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasing 1807.03128.pdf
• evolution_strategies/
  • Deep Neuroevolution Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning ax180420.pdf
• few_shot_learning/
  • Low-Shot Learning with Imprinted Weights ax1804 cvpr18.pdf
  • Matching Networks for One Shot Learning ax171229.pdf
  • Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks 1703.03400 icml17.pdf
  • Prototypical Networks for Few-shot Learning ax1707.pdf
  • Webly Supervised Learning Meets Zero-shot Learning A Hybrid Approach for Fine-grained Classification cvpr18.pdf
• general_value_functions/
  • horde1.pdf
  • HSR12_Abeyruwan.pdf
  • Sherstan_2014_AIROBOT.pdf
  • Sherstan_2016_AGI_preprint.pdf
• generative/
  • #Group meeting Wed Jun 6 1pm Daniel on generative models.pdf
  • A Note on the Inception Score icmlw18 1801.01973.pdf
  • Neural distribution estimation as a two-part problem phd 2023.pdf
  • SEDS a Framework to Generate Stable, Adaptive, Reactive, and Human-Like Robot Reaching Motions 13_1.pdf
  • 3d/
    • Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling.pdf
    • pi-gan periodic implicit generative adversarial networks for 3d-aware image synthesis CVPR 2021.pdf
    • Render for CNN Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views iccv.pdf
  • diffusion/
    • Denoising Diffusion Implicit Models iclr21.pdf
    • Denoising Diffusion Probabilistic Models nips20.pdf
    • Diffusion Models Beat GANs on Image Synthesis 2105.05233.pdf
    • Diffusion Models in Vision A Survey 2209.04747.pdf
    • Generative Modeling by Estimating Gradients of the Data Distribution 1907.05600 nips19.pdf
    • High-Resolution Image Synthesis with Latent Diffusion Models cvpr22 2112.10752.pdf
    • Improved Denoising Diffusion Probabilistic Models icml21.pdf
    • Understanding Diffusion Models A Unified Perspective 2208.11970.pdf
  • GAN/
    • An empirical study on evaluation metrics of generative adversarial networks 1806.07755.pdf
    • Are GANs Created Equal A Large-Scale Study nips18 1711.10337.pdf
    • Generative Adversarial Nets arxiv14.pdf
    • Improved Techniques for Training GANs ax1606.pdf
    • Infogan Interpretable representation learning by information maximizing generative adversarial nets ax1606.03657 nips16.pdf
    • Pros and Cons of GAN Evaluation Measures 1802.03446.pdf
    • Training Generative Adversarial Networks with Limited Data 2006.06676 nips20.pdf
    • Tutorial Generative Adversarial Networks arxiv16 NIPS16.pdf
    • UNROLLED GENERATIVE ADVERSARIAL NETWORKS iclr17 1611.02163.pdf
  • unpaired image translation/
    • Contrastive Learning for Unpaired Image-to-Image Translation 2007.15651.pdf
• graph_theory/
  • Algorithm 447 Efficient algorithms for graph manipulation acm73.pdf
  • An efficient heuristic procedure for partitioning graphs 1970.pdf
  • The Junction Tree Algorithm.pdf
  • The Junction Tree Algorithms.pdf
  • The partition problem mp93.pdf
  • crf/
    • An Introduction to Conditional Random Fields.pdf
    • Conditional Random Fields An Introduction cambridge04.pdf
    • Integer Linear Programming Inference for Conditional Random Fields icml05.pdf
    • Tutorial on Conditional Random Fields for Sequence Prediction.pdf
• HMM/
  • The Forward-Backward Algorithm.pdf
• image_captioning/
  • Deep Visual-Semantic Alignments for Generating Image Descriptionsv cvpr15.pdf
  • Neural Baby Talk 1803.09845 cvpr18.pdf
  • Show and Tell A Neural Image Caption Generator 1411.4555.pdf
  • Show, Attend and Tell Neural Image Caption Generation with Visual Attention xuc15.pdf
  • diffusion/
    • Analog Bits Generating Discrete Data using Diffusion Models with Self-Conditioning iclr23.pdf
  • transformer/
    • Beyond a Pre-Trained Object Detector Cross-Modal Textual and Visual Context for Image Captioning cvprr22.pdf
    • End-to-End Transformer Based Model for Image Captioning aaai22.pdf
    • ExpansionNet v2 Block Static Expansion in fast end to end training for Image Captioning ax2208.pdf
    • GIT A Generative Image-to-text Transformer for Vision and Language ax2212.pdf
    • GRIT Faster and Better Image captioning Transformer Using Dual Visual Features eccv22.pdf
    • Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network aaai21.pdf
    • Meshed-Memory Transformer for Image Captioning CVPR20.pdf
    • mPLUG Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections emnlp22.pdf
    • SeqTR A Simple yet Universal Network for Visual Grounding eccv22.pdf
    • UniTAB Unifying Text and Box Outputs for Grounded Vision-Language Modeling eccv22.pdf
• image_matching/
  • AnchorNet A Weakly Supervised Network to Learn Geometry-sensitive Features For Semantic Matching ax1704.pdf
  • Learning Image Matching by Simply Watching Video eccv16.pdf
  • Local Convolutional Features With Unsupervised Training for Image Retrieval iccv15.pdf
  • siamese_networks_and_learned_similarity/
    • Deep metric learning using Triplet network.pdf
    • Learning a Similarity Metric Discriminatively, with Application to Face Verification 05.pdf
    • Siamese Neural Networks for One-Shot Image Recognition msc-thesis.pdf
    • Siamese Neural Networks for One-shot Image Recognition.pdf
  • similarity_metric/
    • Best-buddies similarity for robust template matching cvpr15.pdf
    • Large scale online learning of image similarity through ranking jmlr10.pdf
• image_processing/
  • Relations between the statistics of natural images and the response properties of cortical cells 87.pdf
  • Statistics of natural images Scaling in the woods 94.pdf
• interpolation/
  • Context-aware Synthesis for Video Frame Interpolation cvpr18 ax1803.10967.pdf
  • Phase-based frame interpolation for video cvpr15.pdf
  • Video Frame Interpolation via Adaptive Convolution ax1703.pdf
  • Video Frame Interpolation via Adaptive Separable Convolution iccv17.pdf
  • notes/
    • Video Frame Interpolation via Adaptive Convolution ax1703.pdf
• labeling/
  • Efficiently Scaling up Crowdsourced Video Annotation ijcv12.pdf
  • LabelMe a database and web-based tool for image annotation. ijcv08.pdf
• machine_learning/
  • Online passive-aggressive algorithms jmlr06.pdf
• manifold embedding/
• misc/
  • A simple method for fitting of bounding rectangle to closed regions pr07.pdf
  • Algorithms for the assignment and transportation problems jsiam57.pdf
  • Bronstein, Bronstein, Kimmel - Numerical Geometry of Nonrigid Shapes.pdf
  • Google’s Hybrid Approach to Research.pdf
  • Hartley, Zisserman - Multiple View Geometry in Computer Vision.pdf
  • Numerical Geometry of Images 2004.pdf
  • The General Theory of General Intelligence A Pragmatic Patternist Perspective 2103.15100.pdf
  • The Multiplicative Weights Update Method A Meta-Algorithm and Applications toc1205.pdf
  • gpu_programming/
    • A GPU-Enabled Solver For Time-Constrained Linear Sum Assignment Problems.pdf
    • GPU-accelerated Hungarian algorithms for the Linear Assignment Problem pc1609.pdf
    • GPU-Based Heuristic Solver for Linear Sum Assignment Problems Under Real-time Constraints 1106.5694.pdf
  • line_intersections/
    • x06-sweepline.pdf
  • math/
    • BODY and SOUL MATHEMATICAL SIMULATION TECHNOLOGY.pdf
    • Computational Differential Equations.pdf
    • Counting Binary Matrices with Given Row and Column Sums 1987.pdf
  • radon_transform/
    • Reconstruction from projections.pdf
    • The Finite Radon Transform - Ball State University.pdf
    • The Radon Transform - Theory and Implementation PhD Thesis.pdf
    • The Radon Transform report07.pdf
    • The Radon Transform.pdf
• MOT/
  • Lifted Disjoint Paths with Application in Multiple Object Tracking 2006.14550 icml20 mot_all_winner.pdf
  • Multi-Object Tracking with Multiple Cues and Switcher-Aware Classification 1901.06129.pdf
  • Quasi-Dense Similarity Learning for Multiple Object Tracking 2006.06664v3.pdf
  • Rethinking the competition between detection and ReID in Multi-Object Tracking 2010.12138v2.pdf
  • 3d/
    • 3D Multi-Object Tracking A Baseline and New Evaluation Metrics 1907.03961v5.pdf
    • 3D Traffic Scene Understanding from Movable Platforms pami14.pdf
    • End-to-end Learning of Multi-sensor 3D Tracking by Detection 1806.11534 icra18.pdf
    • GNN3DMOT Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning 2006.07327v1.pdf
    • JRMOT A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset ax2002.08397.pdf
  • approx_diff/
    • Deep Affinity Network for Multiple Object Tracking ax1810.11780 tpami19.pdf
    • FAMNet Joint Learning of Feature, Affinity and Multi-Dimensional Assignment for Online Multiple Object Tracking iccv19.pdf
    • How To Train Your Deep Multi-Object Tracker 1906.06618v3 cvpr20.pdf
  • association/
    • Data Association for Multi-Object Tracking via Deep Neural Networks sensord1902.pdf
    • Deep Learning for Bipartite Assignment Problems 1908_MPhil.pdf
    • Multi-target Tracking by Rank-1 Tensor Approximation cvpr13.pdf
    • Online Multi-Object Tracking based on Hierarchical Association Framework cvprw16_7.pdf
    • Online multi-object tracking by detection based on generative appearance models cviu16_11.pdf
    • Rank-1 Tensor Approximation for High-Order Association in Multi-target Tracking ijcv19.pdf
    • Towards Real-Time Multi-Object Tracking ax1909.12605v1.pdf
  • baseline/
    • Aerial multi-object tracking by detection using deep association networks ax1909.01547.pdf
    • Deep SORT Simple Online Realtime Tracking with a Deep Association Metric ax1703.07402 icip17.pdf
    • High-Speed Tracking-by-Detection Without Using Image Information avss17.pdf
    • Simple Online and Realtime Tracking ax1707 icip16.pdf
  • batch/
    • A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects ax16_9 [best MT on MOT15].pdf
    • Continuous energy minimization for multitarget tracking tpami14.pdf
    • Learning an image-based motion context for multiple people tracking cvpr14.pdf
    • Multi-target tracking by lagrangian relaxation to min-cost network flow cvpr13.pdf
    • Multi-target Tracking by Rank-1 Tensor Approximation cvpr13.pdf
    • Multiple Object Tracking Using K-Shortest Paths Optimization tpami11.pdf
  • bayesian/
    • Multi-Class Multi-Object Tracking using Changing Point Detection ax16_8.pdf
  • cell/
    • Accurate cell tracking and lineage construction in live-cell imaging experiments with deep learning bioax19.pdf
    • An Objective Comparison of Cell Tracking Algorithms nature methods 2017.pdf
    • DeLTA Automated cell segmentation, tracking, and lineage reconstruction using deep learning ploscb200413.pdf
    • Global linking of cell tracks using the viterbi algorithm_tmi1504.pdf
    • Robust single-particle tracking in live-cell time-lapse sequences. Nature methods, 2008.pdf
  • compressed/
    • MV-YOLO Motion Vector-aided Tracking by Semantic Object Detection ax1806.pdf
  • context/
    • Learning an image-based motion context for multiple people tracking cvpr14.pdf
    • Learning Optimal Parameters for Multi-target Tracking with Contextual Interactions ax1610 ijcv16.pdf
  • deep_learning/
    • Deep Continuous Conditional Random Fields with Asymmetric Inter-object Constraints for Online Multi-object Tracking ax1806.01183.pdf
    • Improving Online Multiple Object tracking with Deep Metric Learning ax1806.07592.pdf
    • Multi-Class Multi-Object Tracking using Changing Point Detection ax160830 eccv16.pdf
    • Multi-Object Tracking with Multiple Cues and Switcher-Aware Classification ax1901.06129.pdf
    • Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanism 1708.02843 iccv17.pdf
    • Online multi-object tracking with dual matching attention networks 1902.00749 eccv18.pdf
    • Real-time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-Identification ax1809.04427.pdf
    • Tracking millions of humans Elsevier_17.pdf
    • Tracking without bells and whistles ax1903.05625 iccv19.pdf
  • detector_fusion/
    • A Novel Multi-Detector Fusion Framework for Multi-Object Tracking ax17_9.pdf
  • dictionary_learning/
    • Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking ax1807.02143.pdf
  • embedded/
    • Deep Learning-Based Multiple Object Visual Tracking on Embedded System for IoT and Mobile Edge Computing Applications 1808.01356.pdf
  • end to end/
  • energy/
    • Continuous energy minimization for multitarget tracking tpami14_1.pdf
  • ensemble/
    • A fast multi-object tracking system using an object detector ensemble ax1908.04349 ColCACI19.pdf
    • To track or to detect an ensemble framework for optimal selection. eccv12.pdf
  • graph/
    • A Graph Transduction Game for Multi-target Tracking ax1806.07227.pdf
    • GSM Graph Similarity Model for Multi-Object Tracking ijcai20.pdf
    • Joint Object Detection and Multi-Object Tracking with Graph Neural Networks 2006.13164 icra21.pdf
    • Subgraph decomposition for multi-object tracking cvpr15.pdf
    • TGCN Time Domain Graph Convolutional Network for Multiple Objects Tracking 2101.01861.pdf
  • joint_detection/
    • A Simple Baseline for Multi-Object Tracking 2004.01888.pdf
    • DEFT Detection Embeddings for Tracking, 2102.02267.pdf
    • Detect to Track and Track to Detect_iccv17.pdf
    • End-to-End Multi-Object Tracking with Global Response Map 2007.06344.pdf
    • FairMOT On the Fairness of Detection and Re-Identification in Multiple Object Tracking 2004.01888v5.pdf
    • Integrated Object Detection and Tracking with Tracklet-Conditioned Detection 1811.11167.pdf
    • Joint Object Detection and Multi-Object Tracking with Graph Neural Networks 2006.13164.pdf
    • MOTS Multi-Object Tracking and Segmentation ax1904 cvpr19.pdf
    • RetinaTrack Online Single Stage Joint Detection and Tracking 2003.13870 cvpr20.pdf
    • Towards Real-Time Multi-Object Tracking ax1909.12605v1 1909.12605 eccv20.pdf
    • Tracking Beyond Detection Learning a Global Response Map for End-to-End Multi-Object Tracking tip21.pdf
    • Tracking Objects as Points 2004.01177 eccv20.pdf
  • metrics/
    • Evaluating Multi-Object Tracking cvpr05.pdf
    • Evaluating multiple object tracking performance the clear mot metrics eurasip08.pdf
    • HOTA A Higher Order Metric for Evaluating Multi-object Tracking sl_open_2010_ijcv2008.pdf
    • Local Metrics for Multi-Object Tracking 2104.02631.pdf
    • Multiple object tracking performance metrics and evaluation in a smart room environment eccvw06.pdf
    • Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking 1609.01775 eccvw16.pdf
    • The clear 2006 evaluation..pdf
  • mht/
    • An Algorithm for Tracking Multiple Targets TAC1979.pdf
    • An efficient implementation of Reid’s multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking pami96.pdf
    • Forty Years of Multiple Hypothesis Tracking.pdf
    • Fundamentals and Advances in Multiple-Hypothesis Tracking .pdf
    • Multiple hypothesis tracking revisited iccv15.pdf
    • The Maximum Weight Independent Set Problem for Data Association in Multiple Hypothesis Tracking 2009.pdf
  • misc/
    • Cyclist Detection, Tracking, and Trajectory Analysis in Urban Traffic Video Data msc_thes1708.pdf
    • Measurement-wise Occlusion in Multi-object Tracking ax1805.08324.pdf
    • Multiple object tracking with context awareness ax1411 1610 phd.pdf
    • Multiple Object Tracking with Kernelized Correlation Filters in Urban Mixed Traffic crv17.pdf
    • PoseTrack Joint Multi-Person Pose Estimation and Tracking_cvpr17.pdf
  • multi_camera/
    • Robust Multi-Modality Multi-Object Tracking 1909.03850 iccv19.pdf
  • network_flow/
    • Deep Network Flow for Multi-Object Tracking cvpr17.pdf
    • Deep Network Flow for Multi-Object Tracking cvpr17_supplemental.pdf
    • FollowMe Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation ax1412 iccv15.pdf
    • Learning a Neural Solver for Multiple Object Tracking 1912.07515 cvpr20.pdf
    • Multi-commodity network flow for tracking multiple people tpami14.pdf
    • Near-online multi-target tracking with aggregated local flow descriptor iccv15.pdf
    • On Pairwise Costs for Network Flow Multi-Object Tracking cvpr15.pdf
    • Target identity-aware network flow for online multiple target tracking cvpr15.pdf
  • notes/
    • A Simple Baseline for Multi-Object Tracking 2004.01888.pdf
    • A_Multi-cut_Formulation_for_Joint_Segmentation_and_Tracking_of_Multiple_Objects.pdf
    • Collaborative Deep Reinforcement Learning for Multi-Object Tracking_eccv18.pdf
    • Deep Affinity Network for Multiple Object Tracking ax1810.11780 tpami19.pdf
    • Deep Network Flow for Multi-Object Tracking cvpr17.pdf
    • Eliminating Exposure Bias and Metric Mismatch in Multiple Object Tracking cvpr19.pdf
    • Exploit the Connectivity Multi-Object Tracking with TrackletNet ax1811.07258 mm19.pdf
    • FAMNet Joint Learning of Feature, Affinity and Multi-Dimensional Assignment for Online Multiple Object Tracking iccv19.pdf
    • High-Speed Tracking-by-Detection Without Using Image Information avss17.pdf
    • HOTA A Higher Order Metric for Evaluating Multi-object Tracking sl_open_2010_ijcv2008.pdf
    • Integrated Object Detection and Tracking with Tracklet-Conditioned Detection 1811.11167.pdf
    • Learning a Neural Solver for Multiple Object Tracking 1912.07515 cvpr20.pdf
    • Learning_to_Track_Online_Multi-object_Tracking_by_Decision_Making__iccv15.pdf
    • mdp_tracking.pdf
    • MOTS Multi-Object Tracking and Segmentation ax1904 cvpr19.pdf
    • Multi-object Tracking with Neural Gating Using Bilinear LSTM_eccv18.pdf
    • NOMT.pdf
    • Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanism 1708.02843 iccv17.pdf
    • Online multi-object tracking with dual matching attention networks 1902.00749 eccv18.pdf
    • Simple Online and Realtime Tracking ax1707 icip16.pdf
    • Simple Unsupervised Multi-Object Tracking 2006.02609.pdf
    • Towards Real-Time Multi-Object Tracking ax1909.12605v1.pdf
    • Tracking by Animation Unsupervised Learning of Multi-Object Attentive Trackers cvpr19 ax1809.03137.pdf
    • Tracking Objects as Points 2004.01177.pdf
    • Tracking without bells and whistles ax1903.05625 iccv19.pdf
    • Tracking_The_Untrackable_Learning_To_Track_Multiple_Cues_with_Long-Term_Dependencies.pdf
    • Unsupervised Person Re-identification by Deep Learning Tracklet Association 1809.02874 eccv18.pdf
  • old/
    • Global data association for multi-object tracking using network flows cvpr08.pdf
    • Learning to associate HybridBoosted multi-target tracker for crowded scene cvpr09.pdf
    • Markov chain monte carlo data association for multi-target tracking tac09.pdf
    • MCMC-based particle filtering for tracking a variable number of interacting targets tpami05.pdf
    • Multi-target tracking by online learned discriminative appearance models. cvpr10.pdf
    • Multiple Object Tracking using K-Shortest Paths pami11.pdf
    • Online multi-target tracking by large margin structured learning accv12.pdf
    • People-Tracking-by-Detection and People-Detection-by-Tracking_cvpr08.pdf
  • PF/
    • Online Multi-target Tracking with Strong and Weak Detections eccv16.pdf
  • reid/
    • Torchreid A Library for Deep Learning Person Re-Identification in Pytorch 1910.10093.pdf
  • reidentification/
    • Attention A Big Surprise for Cross-Domain Person Re-Identification ax1905.12830.pdf
    • Unsupervised Person Re-identification by Deep Learning Tracklet Association 1809.02874 eccv18.pdf
  • review/
    • A Survey on Leveraging Deep Neural Networks for Object Tracking itsc17.pdf
    • A Survey on Leveraging Deep Neural Networks for Object Tracking ppt.pdf
    • Deep Learning in Video Multi-Object Tracking A Survey ax1907.12740.pdf
    • Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking ax1802.06897.pdf
    • Multiple Object Tracking A Literature Review 1409.7618 ax220211 AI21.pdf
    • Real-Time Multiple Object Tracking - A Study on the Importance of Speed ax17_10 thesis.pdf
    • The State of the Art in Multiple Object Tracking Under Occlusion in Video Sequences 2003-ACIVS.pdf
    • Tracking the Trackers An Analysis of the State of the Art in Multiple Object Tracking ax17_4.pdf
    • dubious/
      • A Review of Detection and Tracking of Object from Image and Video Sequences ijcirv13n5_07.pdf
      • A Unified Pipeline for Multiple Object Tracking proj report.pdf
      • Multiple Object Detection and Tracking A Survey 1802.pdf
  • RL/
    • Collaborative Deep Reinforcement Learning for Multi-Object Tracking_eccv18.pdf
    • Learning to Track Online Multi-object Tracking by Decision Making iccv15.pdf
    • Learning to Track Online Multi-Object Tracking by Decision Making_iccv15 supplementary.pdf
    • Multi-Agent_Deep_Reinforcement_Learning_for_Multi-Object_Tracker.pdf
    • Multiobject Tracking in Videos Based on LSTM and Deep Reinforcement Learning hindawi1803.pdf
  • rnn/
    • Deep tracking in the wild End-to-end tracking using recurrent neural networks ijrr17.pdf
    • Eliminating Exposure Bias and Metric Mismatch in Multiple Object Tracking cvpr19.pdf
    • End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks 1604.05091.pdf
    • Multi-object Tracking with Neural Gating Using Bilinear LSTM_eccv18.pdf
    • Multiple Object Tracking in Videos Based on LSTM hindawi.pdf
    • Online Multi-Target Tracking Using Recurrent Neural Networks 1604.03635 aaai17.pdf
    • Tracking of Humans in Video Stream Using LSTM Recurrent Neural Network mml_thes1708.pdf
    • Tracking The Untrackable Learning To Track Multiple Cues with Long-Term Dependencies ax17_4_iccv17.pdf
  • segmentation/
    • Joint tracking and segmentation of multiple targets cvpr15.pdf
    • Learning Multi-Object Tracking and Segmentation from Automatic Annotations cvpr20.pdf
    • MOTS Multi-Object Tracking and Segmentation CVPR19.pdf
    • Segment as points for efficient online multi-object tracking and segmentation eccv20.pdf
    • Track To Detect and Segment An Online Multi-Object Tracker cvpr21.pdf
    • Track, then Decide Category-Agnostic Vision-based Multi-Object Tracking 1712.07920 icra18.pdf
  • siamese/
    • Learning by tracking Siamese CNN for robust target association ax1608 cvprw16.pdf
    • Multi-Object Tracking with Quadruplet Convolutional Neural Networks cvpr17.pdf
    • Online Multi-Object Tracking with Historical Appearance Matching and Scene Adaptive Detection Filtering ax1805.10916 avss18.pdf
    • SiamMOT Siamese Multi-Object Tracking 2105.11595v1.pdf
  • tracklet/
    • Exploit the Connectivity Multi-Object Tracking with TrackletNet ax1811.07258 mm19.pdf
    • Long-term Tracking with Deep Tracklet Association yip2005.pdf
    • Non-Markovian Globally Consistent Multi-Object Tracking_iccv17.pdf
    • SMOT Single-Shot Multi Object Tracking 2010.16031v1.pdf
    • Spatial-Temporal Relation Networks for Multi-Object Tracking 1904.11489.pdf
    • The way they move Tracking multiple targets with similar appearance iccv13.pdf
    • Tracking multi-object using tracklet and Faster R-CNN icdsc16_9.pdf
    • Tracklet association by online target-specific metric learning and coherent dynamics estimation tpami17.pdf
    • Tracklet Association Tracker An End-to-End Learning-based Association Approach for Multi-Object Tracking ax1808.01562.pdf
  • traffic/
    • Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector ax1809.02073.pdf
  • transformers/
    • Global Tracking Transformers cvpr22 2203.13250.pdf
    • Looking Beyond Two Frames End-to-End Multi-Object Tracking Using Spatial and Temporal Transformers 2103.14829.pdf
    • MOTR End-to-End Multiple-Object Tracking with Transformer ax220309.pdf
    • TrackFormer Multi-Object Tracking with Transformers 2101.02702.pdf
    • TransTrack Multiple Object Tracking with Transformer 2012.15460.pdf
    • Unified Transformer Tracker for Object Tracking 2203.15175 cvpr22.pdf
    • ViTT Vision Transformer Tracker sensors-21 mdpi.pdf
  • tubes/
    • Chained-Tracker Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking 2007.14557 eccv20.pdf
    • Simultaneous Detection and Tracking with Motion Modelling for Multiple Object Tracking 2008.08826 eccv20.pdf
    • TrackNet Simultaneous Object Detection and Tracking and Its Application in Traffic Video Analysis 1902.01466.pdf
    • TubeTK Adopting Tubes to Track Multi-Object in a One-Step Training Model 2006.05683 cvpr20.pdf
  • uav/
    • Aerial multi-object tracking by detection using deep association networks ax1909.01547.pdf
  • unsupervised/
    • Self-Supervised Multi-Object Tracking with Cross-Input Consistency nips21.pdf
    • Simple Unsupervised Multi-Object Tracking 2006.02609.pdf
    • Tracking by Animation Unsupervised Learning of Multi-Object Attentive Trackers cvpr19 ax1809.03137.pdf
    • Unsupervised Person Re-identification by Deep Learning Tracklet Association 1809.02874 eccv18.pdf
• motion_prediction/
  • MOTION ESTIMATION USING CONVOLUTIONAL NEURAL NETWORKS.pdf
  • Towards Natural and Accurate Future Motion Prediction of Humans and Animals CVPR19.pdf
  • Transformer Networks for Trajectory Forecasting ax2003.08111.pdf
• Neurosymbolic Programming/
  • Learning Differentiable Programs with Admissible Neural Heuristics nips20 2007.12101.pdf
  • Neurosymbolic Programming.pdf
  • Task Programming Learning Data Efficient Behavior Representations cvpr21.pdf
• neuro_dynamic_programming/
  • Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands cor00.pdf
  • Neuro-Dynamic Programming An Overview 1995 Slides.pdf
  • Neuro-Dynamic Programming An Overview 1995.pdf
• NLP/
  • A Generalist Agent TMLR22.pdf
  • A Survey of Deep Learning Techniques for Neural Machine Translation 2002.07526.pdf
  • Neural Machine Translation in Linear Time ax1610.10099.pdf
  • Training language models to follow instructions with human feedback 2203.02155.pdf
• optical_flow/
  • Beyond Pixels Exploring New Representations and Applications for Motion Analysis phd_mit09.pdf
  • Deep discrete flow accv16.pdf
  • Deep End2End Voxel2Voxel Prediction ax1511 cvprw16.pdf
  • DeepFlow Large Displacement Optical Flow with Deep Matching iccv13.pdf
  • DeepMatching Hierarchical Deformable Dense Matching ijcv16.pdf
  • Dense Optical Flow Prediction From a Static Image iccv15.pdf
  • FlowNet 2.0 Evolution of Optical Flow Estimation with Deep Networks cvpr17.pdf
  • FlowNet Learning Optical Flow With Convolutional Networks iccv15.pdf
  • Optical Flow Estimation using a Spatial Pyramid Network ax161121.pdf
  • PWC-Net CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume ax1709.02371 cvpr18.pdf
  • evaluation/
    • A Database and Evaluation Methodology for Optical Flow iccv07.pdf
    • A database and evaluation methodology for optical flow ijcv11.pdf
    • A naturalistic open source movie for optical flow evaluation eccv12.pdf
  • non_dl/
    • A Duality Based Approach for Realtime TV-L1 Optical Flow dagm07.pdf
    • A Filter Formulation for Computing Real Time Optical Flow ral16.pdf
    • An Efficient Event-Based Optical Flow Implementation in CC++ and CUDA report2015_7.pdf
    • An Improved Algorithm for TV-L1 Optical Flow sgavmn09.pdf
    • EpicFlow Edge-Preserving Interpolation of Correspondences for Optical Flow ax1505 cvpr15.pdf
    • Fast Optical Flow using Dense Inverse Search eccv16.pdf
    • Flow Fields Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation iccv15.pdf
    • High accuracy optical flow estimation based on a theory for warping eccv04.pdf
    • Large displacement optical flow cvpr09.pdf
    • Large displacement optical flow descriptor matching in variational motion estimation tpami11.pdf
    • Learning to Extract Motion from Videos in Convolutional Neural Networks ax1601.pdf
    • Motion Detail Preserving Optical Flow Estimation tpami12.pdf
    • Motion detail preserving optical flow estimation. cvpr10.pdf
    • Parallel Implementation of a Robust Optical Flow Technique techreport CTIM_1_2012.pdf
    • PatchBatch a Batch Augmented Loss for Optical Flow ax1604 cvpr16.pdf
    • SimpleFlow A non-iterative, sublinear optical flow algorithm cgf12.pdf
    • TV-L1 Optical Flow Estimation ipol13.pdf
• optimization/
  • A Review on Bilevel Optimization From Classical to Evolutionary Approaches and Applications ax1705.pdf
  • An overview of bilevel optimization AOR2007.pdf
  • Bilevel Optimization with Nonsmooth Lower Level Problems ssvm2015.pdf
  • ConstrainedAssignment.pdf
  • Evolution Strategies as a Scalable Alternative to Reinforcement Learning ax1709.pdf
  • Linear Programming.pdf
• outlier detection/
  • Snake Validation A PCA-Based Outlier Detection Method spl09.pdf
• perception/
  • ImVoxelNet Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detection wacv22 2106.01178.pdf
  • Reimagining_an_autonomous_vehicle ax2108 wayve.pdf
  • Robust Self-Supervised Extrinsic Self-Calibration 2308.02153 iros23.pdf
  • TractorEYE Vision-based Real-time Detection for Autonomous Vehicles in Agriculture PhD Thesis 2017.pdf
  • fusion/
    • Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection cvprw23 2205.14951.pdf
    • BEVFusion A Simple and Robust LiDAR-Camera Fusion Framework nips22 2205.13790.pdf
    • BEVFusion Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation icra23 2205.13542.pdf
    • LiDAR-as-Camera_for_End-to-End_Driving mdpi sensors Mar 2023.pdf
    • TransFuser Imitation with Transformer-Based Sensor Fusion for Autonomous Driving cvpr21 pami23.pdf
    • TransFusion Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers cvpr22 2203.11496.pdf
  • lidar/
    • PointPillars Fast Encoders for Object Detection from Point Clouds cvpr19 1812.05784.pdf
  • multri camera/
    • BEVDet High-performance Multi-camera 3D Object Detection in Bird-Eye-View 2112.11790.pdf
    • BEVFormer Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers eccv22.pdf
    • Lift, Splat, Shoot Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3D.eccv20 2008.05711.pdf
    • M2BEV Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation 2204.05088.pdf
    • PETR Position Embedding Transformation for Multi-View 3D Object Detection eccv22 .pdf
    • PETRv2 A Unified Framework for 3D Perception from Multi-Camera Images iccv23.pdf
    • TBP-Former Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving cvpr23.pdf
  • path planning/
    • GPT-Driver Learning to Drive with GPT ax2310.01415.pdf
  • radar fusion/
    • A Simple Baseline for BEV Perception Without LiDAR 2206.07959v1.pdf
  • review/
    • 3D Object Detection for Autonomous Driving A Survey 2106.10823.pdf
    • Computer Vision in Self-Steering Tractors machines-10-00129.pdf
    • Delving into the Devils of Bird's-eye-view Perception A Review, Evaluation and Recipe.pdf
• preprocessing/
  • Scale-space and edge detection using anisotropic diffusion tpami90.pdf
• pruning/
  • A comprehensive survey on model compression and acceleration aireview20.pdf
  • A Survey of Model Compression and Acceleration for Deep Neural Networks ax1710.09282.pdf
  • ECC Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model cvpr19.pdf
  • Importance Estimation for Neural Network Pruning_CVPR19.pdf
  • Learning Efficient Convolutional Networks through Network Slimming iccv17.pdf
  • Rethinking the Value of Network Pruning 1810.05270 iclr19.pdf
  • Shallowing deep networks layer-wise pruning based on feature representations tpami18.pdf
  • Structured Pruning of Neural Networks with Budget-Aware Regularization 1811.09332.pdf
  • to_prune_or_not_to_prune_exploring_the_efficacy_of_pruning_for_model_compression.pdf
• radar/
  • Real-Time Detection and Filtering of Chaff Clutter from Single-Polarization Doppler Radar Data ams1305.pdf
• readings/
• reconstruction/
  • A Theory of Fermat Paths for Non-Line-Of-Sight Shape Reconstruction cvpr19.pdf
• registration/
  • A training-free recursive multiresolution framework for diffeomorphic deformable image registration 2202.00675 AI22.pdf
  • An Unsupervised Learning Model for Deformable Medical Image Registration cvpr18.pdf
  • Deep Image Homography Estimation ax1606.pdf
  • Deformable Convolutional Networks iccv17.pdf
  • DRMIME Differentiable Mutual Information and Matrix Exponential for Multi-Resolution Image Registration ax2001.09865.pdf
  • End-to-end weakly-supervised semantic alignment ax1712 cvpr18.pdf
  • Homography Estimation from Image Pairs with Hierarchical Convolutional Networks iccv17.pdf
  • Homography Estimation using Deep Learning for Registering All- 22 Football Video Frames thesis17.pdf
  • Inverse Compositional Spatial Transformer Networks ax1612.pdf
  • MINE Mutual Information Neural Estimation ax1801.04062 icml18.pdf
  • Robust Projective Template Matching tis1610.pdf
  • SRHEN Stepwise-Refining Homography Estimation Network via Parsing Geometric Correspondences in Deep Latent Space 201012.pdf
  • Unsupervised Deep Homography A Fast and Robust Homography Estimation Model ax171229.pdf
  • Unsupervised Deformable Image Registration with Fully Connected Generative Neural Network midl18.pdf
  • Unsupervised deformable image registration with fully connected generative neural network.pdf
  • Unsupervised diffeomorphic cardiac image registration using parameterization of the deformation field 2208.13275 bibm22.pdf
  • WILDCAT Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation cvpr17.pdf
  • 3d/
    • DeepI2P Image-to-Point Cloud Registration via Deep Classification 2104.03501.pdf
  • camera_motion_estimation/
    • Estimating Camera Tilt from Motion without Tracking crv17.pdf
    • Motion from 2D Image Sequences ch9.pdf
    • ROBUST CAMERA MOTION ESTIMATION IN VIDEO SEQUENCES.pdf
    • Unsupervised Camera Motion Estimation and Moving Object Detection in Videos RzDimvip06.pdf
• regression/
  • A mixed-scale dense convolutional neural network for image analysis pnas1901.pdf
  • DenseReg Fully Convolutional Dense Shape Regression In-the-Wild ax1803.02188.pdf
  • Half-CNN A General Framework for Whole-Image Regression .pdf
• reinforcement_learning/
  • actor-critic/
    • Linear off-policy actor-critic icml12.pdf
    • Off-Policy Actor-Critic ax1306.pdf
  • bqn/
    • Bayesian Q-learning aaai98.pdf
    • Bayesian Q-learning with Assumed Density Filtering ax1712 nipsw17.pdf
  • control/
    • A combined reactive and reinforcement learning controller for an autonomous tracked vehicle sd ras12.pdf
    • Coordinated learning based on time-sharing tracking framework and Gaussian regression for continuous multi-agent systems sd eaai15.pdf
    • Model-Based Reinforcement Learning for Infinite-Horizon Approximate Optimal Tracking tnnls17.pdf
    • Model-based reinforcement learning in differential graphical games ax17_2.pdf
    • Model-free linear quadratic tracking control for unmanned helicopters using reinforcement learning icara11.pdf
    • Optimal control of eye-movements during visual search ax17_4.pdf
  • imperfect_models/
    • Reinforcement Learning with Misspecified Model Classes icra13_mit.pdf
  • misc/
    • A new reinforcement learning vehicle control architecture for vision-based road following tvt00.pdf
    • A Tutorial on Thompson Sampling ax1711.pdf
    • Combining Deep Reinforcement Learning and Safety Based Control for Autonomous Driving ax16_12.pdf
    • Deep reinforcement learning with visual attention for vehicle classification tcds16.pdf
    • Deep spatial autoencoders for visuomotor learning icra16.pdf
    • Deep Spatial Autoencoders for Visuomotor Learning ax16_3.pdf
    • Ensemble Learning for Object Recognition and Tracking sl 11.pdf
    • Online Evolution of Deep Convolutional Network for Vision-Based Reinforcement Learning sl sab14.pdf
    • Predicting Future Agent Motions for Dynamic Environments icmla16.pdf
    • Reinforcement learning for hierarchical and modular neural network in autonomous robot navigation jcnn03.pdf
    • Self-learning navigation algorithm for vision-based mobile robots using machine learning algorithms jmst11.pdf
    • The Linear Quadratic Tracking Problem.pdf
  • navigation/
    • DeepTraffic Crowdsourced Hyperparameter Tuning of Deep Reinforcement Learning Systems for Multi-Agent Dense Traffic Navigation ax190103.pdf
  • notes/
    • Classification-based Policy Iteration with a Critic icml11.pdf
    • Learning the Reward Function for a Misspecified Model ax1802.pdf
    • Model Regularization for Stable Sample Rollouts.uai2014.pdf
  • survey/
    • A Short Tutorial on Reinforcement Learning iip05.pdf
    • New Trends in Robotic Reinforcement Learning Single and Multi-robot Case SL 09.pdf
    • Reinforcement learning in feedback control ml11.pdf
    • Reinforcement Learning in Robotics A Survey sl 12.pdf
    • Reinforcement Learning in Robotics A Survey SL 14.pdf
    • Reinforcement learning, conditioning, and the brain Successes and challenges sl cabn12_09.pdf
    • Survey of Model-Based Reinforcement Learning Applications on Robotics sl jirs17.pdf
  • target_following/
    • Robotic Target Tracking with Approximation Space-Based Feedback During Reinforcement Learning SL 07.pdf
    • Target following for an autonomous underwater vehicle using regularized ELM-based reinforcement learning oceans15.pdf
  • unsorted/
    • A self-organizing neural architecture integrating desire, intention and reinforcement learning sd nc10.pdf
    • Algorithms for inverse reinforcement learning icml00.pdf
    • APPRENTICESHIP LEARNING AND REINFORCEMENT LEARNING WITH APPLICATION TO ROBOTIC CONTROL thesis08.pdf
    • Apprenticeship Learning via Inverse Reinforcement Learning icml04.pdf
    • Bayesian Nonparametric Inverse Reinforcement Learning sl ecmlpkdd12.pdf
    • Behavior Adaptation by Means of Reinforcement Learning SL12.pdf
    • Building Machines That Learn and Think Like People arxiv16_11.pdf
    • Control policy with autocorrelated noise in reinforcement learning for robotics ijmlc15.pdf
    • Density Matching Reward Learning ax16_8.pdf
    • Effective learning in dynamic environments by explicit context tracking sl ecml93.pdf
    • Evolution and Learning in an Intrinsically Motivated Reinforcement Learning Robot sl ecal07.pdf
    • Fast gradient-descent methods for temporal-difference learning with linear function approximation icml09.pdf
    • Fuzzy Policy Reinforcement Learning in Cooperative Multi-robot Systems sl jirs07.pdf
    • Gradient Estimation Using Stochastic Computation Graphs arxiv16_1.pdf
    • High-Dimensional Continuous Control Using Generalized Advantage Estimation arxiv 16_9.pdf
    • Hindsight Experience Replay ax180223.pdf
    • Incorporating Expert Advice into Reinforcement Learning Using Constructive Neural Networks sl cnn09.pdf
    • Learning and Querying Fast Generative Models for Reinforcement Learning 1802.pdf
    • Learning Grammars for Architecture-Specific Facade Parsing.IJCV-2016-Gadde-et-al.pdf
    • Learning to Navigate in Complex Environments ax170113.pdf
    • Learning What Data to Learn ax17_2.pdf
    • Model-free reinforcement learning with continuous action in practice acc12.pdf
    • Multi-agent Reinforcement Learning An Overview SL 10.pdf
    • Neural Turing Machines arxiv14_12.pdf
    • Online Learning of a Memory for Learning Rates ax1710.pdf
    • Online Q-Learning using Connectionist Systems 94.pdf
    • Policy gradient methods for reinforcement learning with function approximation nips99.pdf
    • Reinforcement Learning Neural Turing Machines - Revised arxiv16_1.pdf
    • Reinforcement Learning with Neural Networks Tricks of the Trade sl13.pdf
    • Reinforcement Learning with Self-Modifying Policies sl ltl98.pdf
    • Reinforcement Learning with Unsupervised Auxiliary Tasks ax1611.pdf
    • Reluctant Reinforcement Learning sl rdis14.pdf
    • Self-organizing Neural Architecture for Reinforcement Learning sl isnn06.pdf
    • Simple statistical gradient-following algorithms for connectionist reinforcement learning ml92.pdf
    • Toward off-policy learning control with function approximation icml10.pdf
    • Trust Region Policy Optimization arxiv16_6.pdf
    • Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another sl ecml05.pdf
• research_data/
• RNN/
  • A Clockwork RNN ax1402.pdf
  • A Critical Review of Recurrent Neural Networks for Sequence Learning.pdf
  • A Recurrent Latent Variable Model for Sequential Data ax1506.pdf
  • A Theoretically Grounded Application of Dropout in Recurrent Neural Networks ax1610.pdf
  • Adaptive Computation Time for Recurrent Neural Networks ax1603.08983.pdf
  • An Empirical Exploration of Recurrent Network Architectures icml15.pdf
  • Conditional Random Fields as Recurrent Neural Networks iccv15.pdf
  • Generalization without systematicity On the compositional skills of sequence-to-sequence recurrent networks ax1802121.pdf
  • Grid Long Short-Term Memory ax1507.pdf
  • Learning Fast Approximations of Sparse Coding-icml-10.pdf
  • Learning long-term dependencies with gradient descent is difficult tnn94.pdf
  • LEARNING STOCHASTIC RECURRENT NETWORKS x1503.pdf
  • Long-term recurrent convolutional networks for visual recognition and description cvpr15.pdf
  • neural machine translation by jointly learning to align and translate 1409.0473.pdf
  • Neural Programmer Inducing Latent Programs with Gradient Descent ax1511.04834.pdf
  • Neural Turing Machines ax1410.5401.pdf
  • Recurrent nets that time and count IJCNN2000.pdf
  • Recurrent Network Models for Human Dynamics iccv15.pdf
  • Still not systematic after all these years On the compositional skills of sequence-to-sequence recurrent networks 1710.pdf
  • Structural-RNN Deep Learning on Spatio-Temporal Graphs cvpr16 ax16_4.pdf
  • Training Recurrent Neural Networks phd_thesis13.pdf
  • Visualizing and Understanding Recurrent Networks ax15_11.pdf
  • attention/
    • Recurrent Models of Visual Attention arxiv14_6.pdf
    • Show, Attend and Tell Neural Image Caption Generation with Visual Attention ax15_2.pdf
  • BRNN/
    • Bidirectional Recurrent Neural Networks TSP97.pdf
  • ConvLSTM/
    • Convolutional LSTM Network A Machine Learning Approach for Precipitation Nowcasting nips15.pdf
  • generative/
    • DRAW A Recurrent Neural Network For Image Generation 1505.pdf
    • Show, Attend and Tell Neural Image Caption Generation with Visual Attention ax1502.pdf
  • GRU/
    • Depth-Gated Recurrent Neural Networks ax1508.pdf
    • Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling ax1412 nips14.pdf
    • Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.pdf
    • Gated Feedback Recurrent Neural Networks.pdf
    • Learning Phrase Representations using RNN Encoder-Decoder ax14_9 (GRU).pdf
    • Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation emnlp14.pdf
    • On the Properties of Neural Machine Translation Encoder-Decoder Approaches ax1410 ssst8.pdf
  • LSTM/
    • Convolutional LSTM Network A Machine Learning Approach for Precipitation Nowcasting nips15.pdf
    • Grid Long Short-Term Memory ax15_7.pdf
    • LONG SHORT-TERM MEMORY jnc97.pdf
    • LSTM A Search Space Odyssey ax15_3.pdf
    • LSTM A Search Space Odyssey ax1710.pdf
    • Propagating LSTM 3D Pose Estimation based on Joint Interdependency_eccv18.pdf
    • Recurrent Batch Normalization ax1603.09025.pdf
    • Sequence to sequence learning with neural networks nips14.pdf
    • Unsupervised Learning of Video Representations using LSTMs ax1502.04681 icml15.pdf
    • Video (language) modeling a baseline for generative models of natural videos ax1412.6604.pdf
• sensor_fusion/
  • Automatic registration of lidar and optical images of urban scenes cvpr09.pdf
  • AVM LiDAR sensor based lane marking detection method for automated driving on complex urban roads ivs17.pdf
  • Deep Learning for Person Detection in Multi-Spectral Videos mscthes17.pdf
  • Deep Multi-Sensor Lane Detection 1905.01555.pdf
  • Fusion of color images and LiDAR data for lane classification acm2015.pdf
  • FusionLane Multi-Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural Networks 2003.04404.pdf
  • Multi-channel lidar processing for lane detection and estimation its09.pdf
  • Object Detection from a Vehicle using Deep Learning Network and Future Integration with Multi-Sensor Fusion Algorithm 17.pdf
• SLAM/
  • DeepTAM Deep Tracking and Mapping 1808.01900.pdf
  • Efficient ConvNet Feature Extraction with Multiple RoI Pooling for Landmark-based Visual Localization of Autonomous Vehicles mis17.pdf
  • gradSLAM Dense SLAM meets Automatic Differentiation 1910.10672 icra20.pdf
• SOT/
  • Bridging the Gap Between Detection and Tracking A Unified Approach iccv19.pdf
  • Deep Meta Learning for Real-Time Target-Aware Visual Tracking iccv19.pdf
  • Joint Group Feature Selection and Discriminative Filter Learning for Robust Visual Object Tracking iccv19.pdf
  • Ocean Object-aware Anchor-free Tracking 2006.10721 eccv20.pdf
  • Physical Adversarial Textures That Fool Visual Object Tracking iccv19.pdf
  • Skimming-Perusal Tracking A Framework for Real-Time and Robust Long-Term Tracking iccv19.pdf
  • 3d/
    • 3D Pose Tracking Using a Recovered 3D Model jcsc18_ws.pdf
    • A Direct 3D Object Tracking Method Based on Dynamic Textured Model Rendering and Extended Dense Feature Fields tcsvt1707.pdf
    • Fast and Furious Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net_cvpr18.pdf
  • adversarial/
    • Adversarial Feature Sampling Learning for Efficient Visual Tracking ax1809.04741.pdf
    • SINT++ Robust Visual Tracking via Adversarial Positive Instance Generation _cvpr18.pdf
    • VITAL VIsual Tracking via Adversarial Learning_cvpr18.pdf
  • attention/
    • Learning Attentional Policies for Tracking and Recognition in Video icml11.pdf
  • camera/
    • End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning 1808.03405 icml18.pdf
  • color/
    • In Defense of Color-based Model-free Tracking cvpr15.pdf
  • correlation/
    • ATOM Accurate Tracking by Overlap Maximization ax1811.07628 cvpr19.pdf
    • Beyond Correlation Filters Learning Continuous Convolution Operators for Visual Tracking eccv16 ax16_8.pdf
    • Context-Aware Correlation Filter Tracking_cvpr17.pdf
    • Convolutional features for correlation filter based visual tracking iccvw15.pdf
    • Correlation Filters with Limited Boundaries cvpr15 ax1403.7876.pdf
    • Correlation Tracking via Joint Discrimination and Reliability Learning_cvpr18.pdf
    • Correlation Tracking via Robust Region Proposals ax1806.06418 iet18.pdf
    • D3S – A Discriminative Single Shot Segmentation Tracker 1911.08862v1 cvpr20.pdf
    • DCFNet Discriminant Correlation Filters Network for Visual Tracking ax1704.04057.pdf
    • DiMP Learning Discriminative Model Prediction for Tracking ax1904.07220 iccv19.pdf
    • Discriminative Correlation Filter with Channel and Spatial Reliability 1611.08461 ijcv17.pdf
    • ECO Efficient Convolution Operators for Tracking cvpr17 ax17_4.pdf
    • ECO Efficient Convolution Operators for Tracking_cvpr17.pdf
    • End-to-end Flow Correlation Tracking with Spatial-temporal Attention _cvpr18.pdf
    • High-speed Tracking with Multi-kernel Correlation Filters ax1806.05530 cvpr18.pdf
    • High-speed Tracking with Multi-kernel Correlation Filters_cvpr18.pdf
    • Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking ax1807.11071.pdf
    • Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking_eccv18.pdf
    • Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking iccv19.pdf
    • Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Tracking ax1807.11348.pdf
    • Learning Background-Aware Correlation Filters for Visual Tracking_iccv17.pdf
    • Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking_cvpr18.pdf
    • Learning Spatially Regularized Correlation Filters for Visual Tracking iccv16.pdf
    • Long-term Correlation Tracking cvpr15.pdf
    • Multi-Cue Correlation Filters for Robust Visual Tracking_cvpr18.pdf
    • Multi-task Correlation Particle Filter for Robust Object Tracking cvpr17.pdf
    • Overview and methods of correlation filter algorithms in object tracking sl2021.pdf
    • Part-based Visual Tracking via Structural Support Correlation Filter ax1805.09971.pdf
    • PrDiMP Probabilistic Regression for Visual Tracking ax2003.12565 cvpr20.pdf
    • Robust visual tracking using joint scale-spatial correlation filters icip15.pdf
    • State-aware Anti-drift Robust Correlation Tracking ax1806.10759.pdf
    • Visual Object Tracking using Adaptive Correlation Filters cvpr10.pdf
    • Visual Tracking via Spatially Aligned Correlation Filters Network_eccv18.pdf
  • deep_learning/
    • CNNTracker Online discriminative object tracking via deep convolutional neural network ASC16.pdf
    • Context-aware Deep Feature Compression for High-speed Visual Tracking_cvpr18.pdf
    • CREST Convolutional Residual Learning for Visual Tracking_iccv17.pdf
    • Deep Learning of Appearance Models for Online Object Tracking ax16_7.pdf
    • Deep Metric Learning for Visual Tracking tcsvt16_11.pdf
    • Fast Dynamic Convolutional Neural Networks for Visual Tracking ax1807.03132.pdf
    • Learning a deep compact image representation for visual tracking nips13.pdf
    • LEARNING A REAL-TIME GENERIC TRACKER USING CONVOLUTIONAL NEURAL NETWORKS ICME2017.pdf
    • Learning Dynamic Memory Networks for Object Tracking_eccv18.pdf
    • Learning Multi-Domain Convolutional Neural Networks for Visual Tracking cvpr16 ax16_1.pdf
    • Learning Policies for Adaptive Tracking With Deep Feature Cascades_iccv17.pdf
    • Learning regression and verification networks for long-term visual tracking ax1809.04320.pdf
    • Learning Spatial-Aware Regressions for Visual Tracking_cvpr18.pdf
    • Localization-based Visual Tracking with Convolutional Neural Networks icee16.pdf
    • Meta-Tracker Fast and Robust Online Adaptation for Visual Object Trackers 1801.03049 eccv18.pdf
    • Meta-Tracker Fast and Robust Online Adaptation for Visual Object Trackers_eccv18.pdf
    • Modeling and Propagating CNNs in a Tree Structure for Visual Tracking arxiv16 (vot16 winner).pdf
    • Once for All a Two-flow Convolutional Neural Network for Visual Tracking ax16_4.pdf
    • Online Object Tracking Based on CNN with Metropolis-Hasting Re-Sampling acm mm15_9.pdf
    • Online video tracking using collaborative convolutional networks icme16_7.pdf
    • Robust Object Tracking Based on Temporal and Spatial Deep Networks_iccv17.pdf
    • Robust Visual Tracking via Convolutional Networks ax15_8.pdf
    • Robust Visual Tracking via Convolutional Networks Without Training tip16_4.pdf
    • Stochastic Channel Decorrelation Network and Its Application to Visual Tracking ax1807.01103.pdf
    • Unveiling the Power of Deep Tracking ax1804.06833 eccv18.pdf
    • Visual tracking with VG-RAM Weightless Neural Networks sd nc16_3.pdf
    • laser/
      • Deep tracking in the wild End-to-end tracking using recurrent neural networks IJRR1702.pdf
    • old/
      • Design-and-Implementation-of-a-Neural-Network-for-Real-Time-Object-Tracking 2007.pdf
    • point_cloud/
      • Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios 1808.07935.pdf
    • review/
      • A Review of Visual Tracking with Deep Learning aiie16.pdf
    • transfer/
      • Online tracking by learning discriminative saliency map with convolutional neural network icml15 ax15.pdf
      • Transfer learning based visual tracking with Gaussian processes regression eccv14.pdf
      • Transferring Rich Feature Hierarchies for Robust Visual Tracking ax15_4.pdf
  • gaze/
    • Monocular Free-Head 3D Gaze Tracking With Deep Learning and Geometry Constraints_iccv17.pdf
    • Real Time Eye Gaze Tracking With 3D Deformable Eye-Face Model_iccv17.pdf
  • misc/
    • An enhanced adaptive coupled-layer LGTracker ++ iccv13.pdf
    • Combined Image- and World-Space Tracking in Traffic Scenes ax1809.07357.pdf
    • Compressive perceptual hashing tracking sd nc17_5.pdf
    • Learning to Update for Object Tracking ax1806.07078.pdf
    • Non-Rigid Object Tracking via Deformable Patches Using Shape-Preserved KCF and Level Sets_iccv17.pdf
    • One-Class Multiple Instance Learning and Applications to Target Tracking sdl accv12.pdf
    • Parallel Tracking and Verifying A Framework for Real-Time and High Accuracy Visual Tracking_iccv17.pdf
    • Robust Tracking via Weighted Online Extreme Learning Machine 1807.10211.pdf
    • Staple Complementary Learners for Real-Time Tracking ax16_4.pdf
    • Tracking millions of humans in crowded spaces.pdf
    • Tracking with General Regression mva2008.pdf
    • Tracking-by-Segmentation with Online Gradient Boosting Decision Tree iccv15.pdf
    • Understanding and Diagnosing Visual Tracking Systems arxiv15.pdf
    • Visual Object Tracking The Initialisation Problem ax1805.01146 crv18.pdf
    • Visual tracking with sparse correlation filters icip16.pdf
  • motion/
    • Detection free tracking Exploiting motion and topology for segmenting and tracking under entanglement cvpr11.pdf
    • Two-granularity tracking Mediating trajectory and detection graphs for tracking under occlusions eccv12.pdf
  • notes/
    • Action-Decision_Networks_for_Visual_Tracking_with_Deep_Reinforcement_Learning_cvpr17.pdf
    • ATOM Accurate Tracking by Overlap Maximization ax1811.07628 cvpr19.pdf
    • Bridging the Gap Between Detection and Tracking A Unified Approach iccv19.pdf
    • D3S – A Discriminative Single Shot Segmentation Tracker 1911.08862v1 cvpr20.pdf
    • Deep_Reinforcement_Learning_for_Visual_Object_Tracking_in_Videos.pdf
    • DiMP Learning Discriminative Model Prediction for Tracking ax1904.07220 iccv19.pdf
    • High Performance Visual Tracking with Siamese Region Proposal Network_cvpr18.pdf
    • Siam R-CNN Visual Tracking by Re-Detection 1911.12836 cvpr20.pdf
    • SiameseFC.pdf
    • Visual_Tracking_by_Reinforced_Decision_Making_ax17.pdf
  • particle_filter/
    • Learning to track on-the-fly using a particle filter with annealed- weighted QPSO modeled after a singular Dirac delta potential 1806.01396.pdf
  • recurrent_neural_networks/
    • Deep Tracking on the Move Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks ax1704.pdf
    • Deep Tracking Seeing Beyond Seeing Using Recurrent Neural Networks ax1602 aaai16.pdf
    • Deep Tracking Seeing Beyond Seeing Using Recurrent Neural Networks ax16_3 aaai16_2.pdf
    • First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks ax15_11.pdf
    • RATM Recurrent Attentive Tracking Model ax16_4.pdf
    • Re3 Real-Time Recurrent Regression Networks for Object Tracking ax17_3.pdf
    • Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking ax1607.05781 iscas17.pdf
  • registration/
    • Deep 6-DOF Tracking ax1708 tvcg17.pdf
    • Illumination Insensitive Efficient Second-order Minimization for Planar Object Tracking icra17.pdf
    • Robust Tracking of Planar Objects in Low Light and Sudden Illumination Changes 3dv16.pdf
    • Subpixel-Precise Tracking of Rigid Objects in Real-time 1807.01952.pdf
  • reinforcement_learning/
    • Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning cvpr17 supplementary.pdf
    • Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning cvpr17.pdf
    • Action-Driven Visual Object Tracking With Deep Reinforcement Learning tnnls1806.pdf
    • Deep Reinforcement Learning for Visual Object Tracking in Videos ax17_4.pdf
    • Deep Reinforcement Learning with Iterative Shift for Visual Tracking_eccv18.pdf
    • Dual-Agent Deep Reinforcement Learning for Deformable Face Tracking_eccv18.pdf
    • End-to-end Active Object Tracking via Reinforcement Learning ax17_5.pdf
    • Hyperparameter Optimization for Tracking with Continuous Deep Q-Learning_cvpr18.pdf
    • Real-time 'Actor-Critic' Tracking_eccv18.pdf
    • Reinforcement Learning for Robust and Efficient Real-World Tracking icpr10.pdf
    • Tracking as Online Decision-Making Learning a Policy From Streaming Videos With Reinforcement Learning_iccv17.pdf
    • Visual Tracking by Reinforced Decision Making ax17_2.pdf
    • misc/
      • Active tracking and pursuit under different levels of occlusion a two-layer approach sl mva14.pdf
      • Cooperative target searching and tracking via UCT with probability distribution model dsp16.pdf
      • Design and implementation of multi-robot cooperative tracking cscwd10.pdf
      • Experimenting WNN support in object tracking systems sd nc16_3.pdf
      • Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking iros08.pdf
      • Policy learning for autonomous feature tracking sl ar13.pdf
      • Reinforcement learning of cooperative behaviors for multi-robot tracking of multiple moving targets iros05.pdf
      • Reinforcement learning-based feature learning for object tracking icpr04.pdf
      • Tracking strategy based on reinforcement learning and intention inference ccc14.pdf
      • Two steps natural actor critic learning for underwater cable tracking icra10.pdf
  • review/
    • Advances in Deep Learning Methods for Visual Tracking Literature Review and Fundamentals IJAC21 sl.pdf
    • Deep Learning for Visual Tracking A Comprehensive Survey 1912.00535 tits210128.pdf
    • Deep Learning in Visual Tracking A Review TNLS211230.pdf
    • Siamese Visual Object Tracking A Survey ieee2108.pdf
    • Single Object Tracking A Survey of Methods, Datasets, and Evaluation Metrics 2201.13066.pdf
    • The Seventh Visual Object Tracking VOT2019 Challenge Results iccvw19.pdf
  • rgb-d/
    • A Comparative Study of Registration Methods for RGB-D Video of Static Scenes sensors-14-08547.pdf
    • Real-Time Hand Tracking Under Occlusion From an Egocentric RGB-D Sensor_iccv17.pdf
    • Real-time Joint Tracking of a Hand Manipulating an Object from RGB-D Input eccv16.pdf
    • Real-time RGB- D Tracking with Depth Scaling Kernelised Correlation Filters and Occlusion Handling bmvc15.pdf
    • RealtimeHO_ECCV2016_SM.pdf
    • Robust Odometry Estimation for RGB-D Cameras icra13.pdf
  • segmentation/
    • Superpixel-based Tracking-by-Segmentation using Markov Chains_cvpr17.pdf
  • sensor_fusion/
    • Cross-Modal Ranking with Soft Consistency and Noisy Labels for Robust RGB-T Tracking_eccv18.pdf
    • End-to-end Learning of Multi-sensor 3D Tracking by Detection 1806.11534.pdf
    • Real Time Lidar and Radar High-Level Fusion for Obstacle Detection and Tracking with evaluation on a ground truth 1807.11264.pdf
  • siamese/
    • A Twofold Siamese Network for Real-Time Object Tracking_cvpr18.pdf
    • Deeper and Wider Siamese Networks for Real-Time Visual Tracking ax1901.01660 cvpr19.pdf
    • DensSiam End-to-End Densely-Siamese Network with Self-Attention Model for Object Tracking ax1809.02714.pdf
    • Distractor-aware Siamese Networks for Visual Object Tracking ax1808.06048 eccv18.pdf
    • End-To-End Representation Learning for Correlation Filter Based Tracking cvpr17.pdf
    • Fast Online Object Tracking and Segmentation A Unifying Approach ax1812.05050 cvpr19.pdf
    • Fully-Convolutional Siamese Networks for Object Tracking eccv16_9.pdf
    • High Performance Visual Tracking with Siamese Region Proposal Network_cvpr18.pdf
    • Learning Attentions Residual Attentional Siamese Network for High Performance Online Visual Tracking _cvpr18.pdf
    • Learning by tracking Siamese CNN for robust target association ax16_8.pdf
    • Learning Dynamic Siamese Network for Visual Object Tracking_iccv17.pdf
    • Learning the Model Update for Siamese Trackers iccv19.pdf
    • Learning to Track at 100 FPS with Deep Regression Networks arxiv16.pdf
    • Multi-Branch Siamese Networks with Online Selection for Object Tracking ax1808.07349.pdf
    • Once for All a Two-flow Convolutional Neural Network for Visual Tracking ax1604.07507.pdf
    • Siam R-CNN Visual Tracking by Re-Detection 1911.12836 cvpr20.pdf
    • Siamese Instance Search for Tracking cvpr16 ax16_5.pdf
    • SiamRPN++ Evolution of Siamese Visual Tracking with Very Deep Networks ax1812.11703 cvpr19.pdf
    • SiamVGG Visual Tracking using Deeper Siamese Networks ax1902.02804.pdf
    • Structured Siamese Network for Real-Time Visual Tracking_eccv18.pdf
    • Triplet Loss in Siamese Network for Object Tracking_eccv18.pdf
    • Understanding Siamese Networks for Visual Object Tracking msc thes 20.pdf
  • trajectory/
    • Learning Social Etiquette Human Trajectory Prediction In Crowded Scenes eccv16.pdf
    • PathTrack Fast Trajectory Annotation With Path Supervision_iccv17.pdf
    • Social LSTM Human Trajectory Prediction in Crowded Spaces cvpr16.pdf
    • Who are you with and where are you going cvpr11.pdf
  • transformers/
    • MMTrack Towards Unified Token Learning for Vision-Language Tracking tcsvt2308 2308.14103.pdf
    • SeqTrack Sequence to Sequence Learning for Visual Object Tracking cvpr23.pdf
    • Transformer Tracking cvpr21.pdf
  • unsorted/
  • unsupervised/
    • Tracking Emerges by Colorizing Videos ax1806.09594 eccv18.pdf
    • Unsupervised Deep Tracking ax1904.01828 cvpr19.pdf
• static_detection/
  • EfficientDet_Scalable and efficient object detection.pdf
  • Generalized Intersection over Union A Metric and A Loss for Bounding Box Regression 1902.09630 cvpr19.pdf
  • Objects as Points ax1904.07850.pdf
  • Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks aaai19.pdf
  • SpineNet Learning Scale-Permuted Backbone for Recognition and Localization 1912.05027 cvpr20.pdf
  • Towards Deeper Understanding of Camouflaged Object Detection 2205.11333 cvpr21.pdf
  • Training Region-based Object Detectors with Online Hard Example Mining 1604.03540 cvpr16.pdf
  • anchor_free/
    • Bottom-up object detection by grouping extreme and center points 1901.08043.pdf
    • Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection 1912.02424 cvpr20.pdf
    • CornerNet Detecting Objects as Paired Keypoints ax1903 ijcv19.pdf
    • End-to-End Object Detection with Transformers ax200528.pdf
    • FCOS Fully Convolutional One-Stage Object Detection ax1908 iccv19.pdf
    • Feature Selective Anchor-Free Module for Single-Shot Object Detection ax1903.00621 cvpr19.pdf
    • FoveaBox Beyond Anchor-based Object Detector ax1904.03797.pdf
    • Objects as Points ax1904.07850.pdf
    • RepPoints Point Set Representation for Object Detection 1904.11490 iccv19.pdf
  • animal/
    • An Animal Detection Pipeline for Identification wacv18.pdf
    • Animal Recognition and Identification with Deep Convolutional Neural Networks for Automated Wildlife Monitoring DSAA17.pdf
    • Animal Recognition System Based on Convolutional Neural Network aeee17.pdf
    • Automated Detection and Recognition of Wildlife Using Thermal Cameras sensors14.pdf
    • Automated Detection of Animals in Context to Indian Scenario isms14 .pdf
    • Automatic Detection and Recognition of Individuals in Patterned Species ecmlpkdd17_iiitd.pdf
    • Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning ax171115.pdf
    • From Tiger to Panda Animal Head Detection tip1106.pdf
    • Night vision animal detection ivsp14.pdf
    • Semantic Part Segmentation using Compositional Model combining Shape and Appearance 1412.6124.pdf
    • Synthetic Examples Improve Generalization for Rare Classes ax1904.05916.pdf
    • Where's the Bear - Automating Wildlife Image Processing Using IoT and Edge Cloud Systems ioTDI17.pdf
    • aerial/
      • Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems ax1701.01611 ijrs.pdf
      • Background Categorization for Automatic Animal Detection in Aerial Videos Using Neural Networks annpr16_sl.pdf
      • Best Practices to Train Deep Models on Imbalanced Datasets—A Case Study on Animal Detection in Aerial Imagery.pdf
      • Detecting animals in African Savanna with UAVs and the crowds ax1710 rse1710_sd.pdf
      • Detecting mammals in UAV images Best practices to address a substantially imbalanced dataset with deep learning rse18_sd.pdf
      • Fast animal detection in UAV images using convolutional neural networks igarrs17.pdf
      • Half a Percent of Labels is Enough Efficient Animal Detection in UAV Imagery using Deep CNNs and Active Learning tgrs19 ax1907.07319.pdf
      • Motion Based Animal Detection in Aerial Videos pcs16_sd.pdf
    • camera_trap/
      • A novel system for automatic detection and classification of animal elektro14.pdf
      • A Support Vector Machine with Gabor Features for Animal Intrusion Detection in Agriculture Fields pcs18_sd.pdf
      • Animal Detection From Highly Cluttered Natural Scenes Using Spatiotemporal Object Region Proposals and Patch Verification tim1610.pdf
      • AnimalFinder A semi-automated system for animal detection in time-lapse camera trap images ei1611_sd.pdf
      • Automatic Recognition of Mammal Genera on Camera-Trap Images using Multi-Layer Robust Principal Component Analysis and Mixture Neural Networks ax1705.02727.pdf
      • Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning pnas18.pdf
      • Camera-trap images segmentation using multi-layer robust principal component analysis ax1701.08180.pdf
      • Deep convolutional neural network based species recognition for wild animal monitoring icip14.pdf
      • Deep Learning Object Detection Methods for Ecological Camera Trap Data ax1803.10842.pdf
      • Fast human-animal detection from highly cluttered camera-trap images using joint background modeling and deep learning classification iscas17.pdf
      • Identifying animal species in camera trap images using deep learning and citizen science 2019-Methods_in_Ecology_and_Evolution.pdf
      • Object detection from dynamic scene using joint background modeling and fast deep learning classification jvcir1808_sd.pdf
      • Omni-supervised joint detection and pose estimation for wild animals orl1811_sd.pdf
      • Past, Present, and Future Approaches Using Computer Vision for Animal Re-Identification from Camera Trap Data ax1811.07749.pdf
      • Recognition in Terra Incognita ax1807.04975 eccv178.pdf
      • Towards Automatic Wild Animal Detection in Low Quality Camera-Trap Images Using Two-Channeled Perceiving Residual Pyramid Networks iccvw17.pdf
      • Wild Animal Detection from Highly Cluttered Forest Images Using Deep Residual Networks ihci18_sl.pdf
      • Wild Animal Detection Using Deep Convolutional Neural Network cvip17_sl.pdf
    • datasets/
    • no_vision/
      • A standardised framework for analysing animal detections from automated tracking arrays an_bio1812_sl.pdf
      • Animal intrusion detection based on convolutional neural network iscit17.pdf
      • Animal-vehicle collisions in Texas How to protect travelers and animals on roadways aap1910_sd.pdf
      • How do amplitude spectra influence rapid animal detection vr0910_sd.pdf
      • Internet of Things Applications Animal Monitoring with Unmanned Aerial Vehicle ax1610.05287.pdf
      • Reducing the threat of wildlife-vehicle collisions during peak tourism periods using a Roadside Animal Detection System aap1712_sd.pdf
    • video/
      • Amur Tiger Re-identification in the Wild ax1906.05586.pdf
      • Analysing animal behaviour in wildlife videos using face detection and tracking visp06_iet.pdf
      • BioSense Real-Time Object Tracking for Animal Movement and Behavior Research aipr18.pdf
      • BioTracker An Open-Source Computer Vision Framework for Visual Animal Tracking ax1803.07985.pdf
      • Building models of animals from video tpami0608.pdf
      • idtracker.ai Tracking all individuals in large collectives of unmarked animals ax1803.04351.pdf
      • MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology bioax190330.pdf
      • Tracktor Image‐based automated tracking of animal movement and behaviour 190215.pdf
  • anomaly/
  • augmentation/
    • Learning Data Augmentation Strategies for Object Detection ax1906.11172.pdf
  • background_subtraction/
    • ANOMALY DETECTION IN SURVEILLANCE VIDEOS USING DEEP RESIDUAL NETWORKS mscthes1702.pdf
  • boundary/
    • Contour Detection and Hierarchical Image Segmentation tpami1105.pdf
    • ContourGAN Image Contour Detection with Generative Adversarial Encoder-Decoder Networks kbs190115_sd.pdf
    • Convolutional Oriented Boundaries eccv16.pdf
    • Convolutional Oriented Boundaries From Image Segmentation to High-Level Tasks tpami18 ax1704.pdf
    • Crisp Boundary Detection Using Pointwise Mutual Information eccv14.pdf
    • High-for-Low and Low-for-High Efficient Boundary Detection From Deep Object Features and its Applications to High-Level Vision iccv15.pdf
    • Holistically-Nested Edge Detection ax1510 iccv15.pdf
  • cell/
    • Output Encoding by Compressed Sensing for Cell Detection with Deep Convnet aaai19.pdf
    • Training Convolutional Neural Networks and Compressed Sensing End-to-End for Microscopy Cell Detection ax1810.03075.pdf
  • classic/
    • dpm-slides-ross-girshick.pdf
    • Object Detection with Discriminatively Trained Part Based Models tpami10.pdf
    • Regionlets for Generic Object Detection iccv13.pdf
  • crop/
    • Towards Infield Navigation leveraging simulated data for crop row detection 2204.01811.pdf
  • deep_learning/
    • Acquisition of Localization Confidence for Accurate Object Detection 1807.11590 eccv18.pdf
    • Bag of Freebies for Training Object Detection Neural Networks ax190412.pdf
    • Beyond Skip Connections Top-Down Modulation for Object Detection ax1612.06851.pdf
    • Deep Neural Networks for Object Detection nips13.pdf
    • Deep Regionlets for Object Detection ax1712.pdf
    • Enriching object detection with 2D-3D registration and continuous viewpoint estimation cvpr15.pdf
    • Learning Region Features for Object Detection ax180319.pdf
    • LSDA Large scale detection through adaptation nips14 ax14_11.pdf
    • Object Detection Networks on Convolutional Feature Maps ax1608 tpami16.pdf
    • OverFeat Integrated Recognition, Localization and Detection using Convolutional Networks ax1402 iclr14.pdf
    • Relation Networks for Object Detection ax171130 cvpr18.pdf
    • Scale-Transferrable Object Detection cvpr18.pdf
    • Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition ax150423 tpami15.pdf
    • Subcategory-aware Convolutional Neural Networks for Object Proposals and Detection wacv17 ax17_3.pdf
  • domain_adaptation/
    • Adapting Object Detectors via Selective Cross-Domain Alignment cvpr19.pdf
    • Diversify and Match A Domain Adaptive Representation Learning Paradigm for Object Detection cvpr19.pdf
    • Domain Adaptive Faster R-CNN for Object Detection in the Wild cvpr18.pdf
    • Strong-Weak Distribution Alignment for Adaptive Object Detection cvpr19.pdf
    • Unsupervised Domain adaptation in object detection.pdf
  • fence/
    • Automatic Fence Segmentation in Videos of Dynamic Scenes cvpr16.pdf
    • Automatic inpainting by removing fence-like structures in RGBD images mva1410_springer.pdf
    • Deep learning based fence segmentation and removal from an image using a video sequence ax161021.pdf
    • Fence-like Quasi-periodic Texture Detection in Images 14.pdf
    • Image De-fencing Revisited accv12.pdf
    • Image de-fencing using histograms of oriented gradients sivp1803_springer.pdf
    • My camera can see through fences A deep learning approach for image de-fencing acpr15.pdf
  • grasp/
    • deep learning for detecting robotic grasps ijrr15.pdf
    • deep learning for detecting robotic grasps rss09.pdf
  • hard_negative_mining/
    • Bootstrapping Face Detection with Hard Negative Examples ax1608.pdf
    • Training Region-based Object Detectors with Online Hard Example Mining ax1604.03540 cvpr16.pdf
  • human/
    • Deep Learning for Human Part Discovery in Images icra16.pdf
  • instance_segmentation/
    • Mask R-CNN ax17_4 iccv17.pdf
    • Mask R-CNN ax180124.pdf
    • MaskLab Instance Segmentation by Refining Object Detection With Semantic and Direction Features_cvpr18.pdf
    • Pseudo Mask Augmented Object Detection cvpr18.pdf
  • medical/
    • Retinal Glaucoma Detection Using Deep Learning Algorithm Tanu.pdf
  • mobile/
    • EfficientDet Scalable and Efficient Object Detection 1911.09070 cvpr20.pdf
    • MnasFPN Learning Latency-aware Pyramid Architecture for Object Detection on Mobile Devices 1912.01106.pdf
    • MobileDets Searching for Object Detection Architectures for Mobile Accelerators 2004.14525 cvpr21.pdf
    • MobileNetV2 Inverted Residuals and Linear Bottlenecks ax180402.pdf
    • Squeezedet Unified, small, low power fully convolutional neural net- works for real-time object detection for autonomous driving cvprw17.pdf
  • notes/
    • Bottom-up object detection by grouping extreme and center points 1901.08043.pdf
    • Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection 1912.02424 cvpr20.pdf
    • CornerNet Detecting Objects as Paired Keypoints ax1903 ijcv19.pdf
    • DSSD.pdf
    • End-to-end object detection with Transformers ax200528.pdf
    • Faster_R-CNN.pdf
    • FCOS Fully Convolutional One-Stage Object Detection ax1908 iccv19.pdf
    • Feature Selective Anchor-Free Module for Single-Shot Object Detection ax1903.00621 cvpr19.pdf
    • focal_loss.pdf
    • FoveaBox Beyond Anchor-based Object Detector ax1904.03797.pdf
    • FPN.pdf
    • Generalized Intersection over Union A Metric and A Loss for Bounding Box Regression 1902.09630 cvpr19.pdf
    • IOU-Net.pdf
    • LSDA Large scale detection through adaptation nips14 ax14_11.pdf
    • Mask R-CNN ax17_4 iccv17.pdf
    • Objects as Points ax1904.07850.pdf
    • OverFeat Integrated Recognition, Localization and Detection using Convolutional Networks ax1402 iclr14.pdf
    • RepPoints Point Set Representation for Object Detection 1904.11490 iccv19.pdf
    • RFCN.pdf
    • Scalable Object Detection Using Deep Neural Networks cvpr14.pdf
    • Selective Search for Object Recognition ijcv2013.pdf
    • SNIPER Efficient Multi-Scale Training ax181213 nips18.pdf
    • SSD.pdf
    • TCNN.pdf
    • YOLO9000 Better, Faster, Stronger ax16_12.pdf
    • YOLOv3 An Incremental Improvement ax180408.pdf
    • YOLOV4_Optimal Speed and Accuracy of Object Detection ax200423.pdf
    • You Only Look Once Unified, Real-Time Object Detection ax1605.pdf
  • post_processing/
    • Assessing post-detection filters for a generic pedestrian detector in a tracking-by-detection scheme avss17.pdf
    • Soft-NMS -- Improving Object Detection With One Line of Code 1704.04503 iccv17.pdf
  • rare/
    • Meta-Learning to Detect Rare Objects iccv19.pdf
    • Training Rare Object Detection in Satellite Imagery with Synthetic GAN Images cvprw21.pdf
  • RCNN/
    • A MultiPath Network for Object Detection ax1604.02135 facebook.pdf
    • An Analysis of Scale Invariance in Object Detection ­ SNIP cvpr18.pdf
    • Cascade R-CNN Delving into High Quality Object Detection cvpr18 1712.00726.pdf
    • Cascade R-CNN High Quality Object Detection and Instance Segmentation tpami21 1906.09756.pdf
    • Context R-CNN Long Term Temporal Context for Per-Camera Object Detection 1912.03538 cvpr20.pdf
    • Fast R-CNN ax1509 iccv15.pdf
    • Faster R-CNN Towards Real-Time Object Detection with Region Proposal Networks nips15 arxiv15.pdf
    • Faster R-CNN Towards Real-Time Object Detection with Region Proposal Networks tpami17 ax16_1.pdf
    • Light-Head R-CNN In Defense of Two-Stage Object Detector cvpr18 1711.07264.pdf
    • Multi-Scale Location-Aware Kernel Representation for Object Detection_cvpr18.pdf
    • Object Detection Networks on Convolutional Feature Maps ax1608 tpami17.pdf
    • PVANet Lightweight Deep Neural Networks for Real-time Object Detection ax1612 nipsw16.pdf
    • R-FCN-3000 at 30fps Decoupling Detection and Classification cvpr18.pdf
    • Region-Based Convolutional Networks for Accurate Object Detection and Segmentation tpami16_1.pdf
    • RFCN-Object Detection via Region-based Fully Convolutional Networks nips16.pdf
    • Rich feature hierarchies for accurate object detection and semantic segmentation ax141022 cvpr14.pdf
    • SNIPER Efficient Multi-Scale Training ax181213 nips18.pdf
    • Sparse R-CNN End-to-End Object Detection with Learnable Proposals cvpr21 2011.12450.pdf
  • region_proposal/
    • Deep Reinforcement Learning of Region Proposal Networks for Object Detection_cvpr18.pdf
    • Edge boxes Locating object proposals from edges eccv14.pdf
    • Multiscale Combinatorial Grouping cvpr14.pdf
    • Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation ax2015_v3 tpami16.pdf
    • Scalable Object Detection Using Deep Neural Networks cvpr14.pdf
    • Scalable, High-Quality Object Detection ax1512.pdf
    • Selective Search for Object Recognition ijcv2013.pdf
    • Selective Search for Object Recognition ppt ijcv12.pdf
  • retinanet/
    • Consecutive Feature Network for Object Detection icma18.pdf
    • Fast Feature pyramid for object detection tpami14.pdf
    • Feature Pyramid Networks for Object Detection ax170419.pdf
    • Focal Loss for Dense Object Detection ax180207 iccv17.pdf
  • review/
    • Application of Deep Learning for Object Detection pcs18_sd_kiit.pdf
    • Deep learning for class-generic object detection 1312.6885.pdf
    • Deep Learning for Generic Object Detection A Survey ax1809.02165 ijcv19.pdf
    • Speed accuracy trade-offs for modern convolutional object detectors ax1704 cvpr17.pdf
  • RNN/
    • Inside-Outside Net Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks 1512.04143 cvpr16.pdf
  • road/
    • A New Performance Measure and Evaluation Benchmark for Road Detection Algorithms ITSC2013l.pdf
    • Deep Learning for Robust Road Object Detection msc_thes17.pdf
    • Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset.pdf
    • ROAD The ROad event Awareness Dataset for Autonomous Driving 2102.11585.pdf
  • sensor_fusion/
  • single_stage/
    • DeNet Scalable Real-time Object Detection with Directed Sparse Sampling iccv17 ax1703.10295.pdf
  • skeleton/
    • DeepSkeleton Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images ax1707 tpami17.pdf
    • Hi-Fi Hierarchical Feature Integration for Skeleton Detection ijcai18.pdf
    • Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs ax1604 cvpr16.pdf
  • small/
    • An Evaluation of Deep Learning Methods for Small Object Detection hindawi20.pdf
  • SSD/
    • Context-Aware Single-Shot Detector 1707.08682 wacv18.pdf
    • Deep Feature Pyramid Reconfiguration for Object Detection 1808.07993 eccv18.pdf
    • DSSD Deconvolutional Single Shot Detector ax1701.06659.pdf
    • Enhancement of SSD by concatenating feature maps for object detection 1705.09587.pdf
    • Extend the shallow part of Single Shot MultiBox Detector via Convolutional Neural Network 1801.05918.pdf
    • FSSD Feature Fusion Single Shot Multibox Detector 1712.00960.pdf
    • MDSSD Multi-scale Deconvolutional Single Shot Detector for Small Objects ax1805.07009.pdf
    • Single-Shot Object Detection With Enriched Semantics_cvpr18.pdf
    • Single-Shot Refinement Neural Network for Object Detection_cvpr18.pdf
    • SSD Single Shot MultiBox Detector eccv16_ax16_12.pdf
  • text/
    • An Anchor-Free Region Proposal Network for Faster R-CNN based Text Detection Approaches 1804.09003.pdf
    • Unknown-box Approximation to Improve Optical Character Recognition Performance 2105.07983 icdar21.pdf
    • Unknown-box Approximation to Improve Optical Character Recognition Performance _202105_MSc thesis.pdf
  • transformers/
    • Deformable DETR Deformable Transformers for End-to-End Object Detection 2010.04159 iclr21.pdf
    • Efficient DETR Improving End-to-End Object Detector with Dense Prior 2104.01318.pdf
    • End-to-End Object Detection with Transformers ax200528.pdf
    • Label2Label A Language Modeling Framework for Multi-Attribute Learning eccv22.pdf
    • OFA Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework icml22.pdf
    • Pix2seq A Language Modeling Framework for Object Detection iclr22.pdf
    • Rethinking transformer-based set prediction for object detection iccv21 2011.10881.pdf
  • vehicle/
    • Evolving Boxes for Fast Vehicle Detection icme13.pdf
  • weak_supervision/
    • End-to-End Semi-Supervised Object Detection with Soft Teacher 2106.09018v2.pdf
    • W2F A Weakly-Supervised to Fully-Supervised Framework for Object Detection cvpr18-supp.pdf
    • W2F A Weakly-Supervised to Fully-Supervised Framework for Object Detection cvpr18.pdf
  • yolo/
    • Complex-YOLO An Euler-Region-Proposal for Real-time 3D Object Detection on Point Clouds ax1803.06199.pdf
    • YOLO-ReT Towards High Accuracy Real-time Object Detection on Edge GPUs 2110.13713 wacv22.pdf
    • YOLO9000 Better, Faster, Stronger ax16_12.pdf
    • YOLOv3 An Incremental Improvement ax180408.pdf
    • YOLOV4_Optimal Speed and Accuracy of Object Detection ax200423.pdf
    • You Only Look at One Sequence Rethinking Transformer in Vision through Object Detection 2106.00666 nips21.pdf
    • You Only Look Once Unified, Real-Time Object Detection ax1605.pdf
  • zero_shot/
    • Zero-Shot Detection ax1903 ax1803.07113 tcsvt.pdf
    • Zero-Shot Object Detection ax1804.04340 eccv18.pdf
    • Zero-Shot Object Detection by Hybrid Region Embedding bmvc18 ax1805.06157.pdf
    • Zero-Shot Object Detection Learning to Simultaneously Recognize and Localize Novel Concepts ax1803.06049 accv18.pdf
• static_segmentation/
  • Efficient Shallow Network for River Ice Segmentation remotesensing 220515.pdf
  • Fast Large-Scale Spectral Clustering via Explicit Feature Mapping TC19 NR.pdf
  • Fast-SCNN Fast Semantic Segmentation Network 1902.04502.pdf
  • Fully Convolutional Networks for Semantic Segmentation ax1504 cvpr15.pdf
  • ICENET A Semantic Segmentation Deep Network for River Ice by Fusing Positional and Channel-Wise Attentive Features remotesensing-12-00221.pdf
  • ICNet for Real-Time Semantic Segmentation on High-Resolution Images ax1704.pdf
  • Instance-aware Semantic Segmentation via Multi-task Network Cascades 1512.04412.pdf
  • Interactive image segmentation by maximal similarity based region merging pr09.pdf
  • Learning from Synthetic Data Addressing Domain Shift for Semantic Segmentation ax1711 cvpr18.pdf
  • Multi-Scale Context Aggregation by Dilated Convolutions ax160430 iclr16.pdf
  • ParseNet Looking Wider to See Better ax1511 iclr16.pdf
  • PixelNet Representation of the pixels, by the pixels, and for the pixels. 17.pdf
  • Segment Anything 2304.02643.pdf
  • Two layer Ensemble of Deep Learning Models for Medical Image Segmentation 2104.04809.pdf
  • What's the Point Semantic Segmentation with Point Supervision ax1607 eccv16.pdf
  • deeplab/
    • Auto-DeepLab Hierarchical Neural Architecture Search for Semantic Image Segmentation ax1904 cvpr19.pdf
    • DeepLab Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs ax17_5.pdf
    • DeepLab Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs} ax16.pdf
    • Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation ax180308.pdf
    • Rethinking Atrous Convolution for Semantic Image Segmentation ax1706.05587.pdf
    • Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs ax16_6 iclr15.pdf
    • Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation ax15_11.pdf
  • few_shot/
    • Few-Shot Segmentation Propagation with Guided Networks ax1806.07373.pdf
  • instance/
    • A Unified Sequence Interface for Vision Tasks nips22.pdf
    • Deep Learning based Food Instance Segmentation using Synthetic Data 2107.07191v2.pdf
    • FCOS Fully Convolutional One-Stage Object Detection 1904.01355.pdf
    • Fully Convolutional Instance-aware Semantic Segmentation ax1704 cvpr17.pdf
    • Instance-aware Semantic Segmentation via Multi-task Network Cascades ax1512.04412.pdf
    • Instance-sensitive Fully Convolutional Networks ax1603.08678.pdf
    • Large-scale interactive object segmentation with human annotators ax1903.10830 cvpr19.pdf
    • Mask Scoring R-CNN 1903.00241.pdf
    • RetinaMask Learning to predict masks improves state-of-the-art single-shot detection for free 1901.03353.pdf
    • Rock Instance Segmentation from Synthetic Images for Planetary Exploration Missions_asre21.pdf
    • The surprising impact of mask-head architecture on novel class segmentation 2104.00613.pdf
  • medical_imaging/
    • Deep Fusion Net for Multi-Atlas Segmentation Application to Cardiac MR Images.pdf
    • End-to-end learning of convolutional neural net and dynamic programming for left ventricle segmentation mlr20.pdf
  • misc/
    • Omnimatte Associating Objects and Their Effects in Video 2105.06993.pdf
  • panoptic/
    • Panoptic Segmentation 1801.00868 cvpr19.pdf
    • Visual Recognition by Request cvpr23.pdf
  • proposal/
    • Learning to Refine Object Segments ax1608 eccv16.pdf
    • Learning to Segment Object Candidates ax1509 nips15.pdf
  • road/
    • Superpixel clustering with deep features for unsupervised road segmentation ax1711.pdf
  • segnet/
    • SegNet A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation pami17.pdf
    • SegNet A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling ax1505.pdf
  • tokens/
    • All in Tokens Unifying Output Space of Visual Tasks via Soft Token iccv23.pdf
    • Obj2Seq Formatting Objects as Sequences with Class Prompt for Visual Tasks nips22.pdf
    • Point2Seq Detecting 3D Objects As Sequences cvpr22.pdf
    • PolyFormer Referring Image Segmentation As Sequential Polygon Generation cvpr23.pdf
    • Unified-IO A Unified Model for Vision, Language, and Multi-Modal Tasks 2206.08916.pdf
    • UViM A Unified Modeling Approach for Vision with Learned Guiding Codes nips22.pdf
  • unet/
    • U-Net Convolutional Networks for Biomedical Image Segmentation ax1509 miccai15.pdf
• stereo/
  • Efficient Deep Learning for Stereo Matching cvpr16.pdf
• tools/
  • A new approach towards implementing artificial neural networks.pdf
  • A Survey of Semantic Image and Video Annotation Tools 2011.pdf
  • matconvnet-manual.pdf
  • MXNet A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems nips15.pdf
  • TensorFlow 15_9.pdf
• traffic_monitoring/
  • A computer vision system for the detection and classification of vehicles at urban road intersections paa05.pdf
  • A real-time computer vision system for vehicle tracking and traffic surveillance tret98.pdf
  • A taxonomy and analysis of camera calibration methods for traffic monitoring applications itst10.pdf
  • An Overview of Image processing for traffic applications iosr14.pdf
  • Automated Road Safety Analysis Using Video Sensors trb07.pdf
  • Biologically Inspired Composite Vision System for Multiple Depth-of-field Vehicle Tracking and Speed Detection accvw14.pdf
  • Biologically inspired composite vision system for traffic monitoring icca16.pdf
  • Biologically-Inspired Long-Range Traffic Monitoring System with Basler ace USB 3.0 Camera.pdf
  • Camera calibration for urban traffic scenes Practical issues and a robust approach trbam10.pdf
  • Computer Vision on Embedded Sensors for Traffic Flow Monitoring itsc15.pdf
  • Learning, Modeling, and Understanding Vehicle Surround Using Multi-Modal Sensing dissertation.pdf
  • Matching vehicles under large pose transformations using approximate 3D models and piecewise MRF model cvpr08.pdf
  • Real-time Vehicle Detection and Tracking Using Stereo Vision and Multi-View AdaBoost itsc-11.pdf
  • Road intersection monitoring from video with large perspective deformation itswc14.pdf
  • Street Viewer An Autonomous Vision Based Traffic Tracking System sensors16.pdf
  • Traffic monitoring and accident detection at intersections itst00.pdf
  • ViBe A universal background subtraction algorithm for video sequences tip11.pdf
  • Vision-based scale-adaptive vehicle detection and tracking for intelligent traffic monitoring robio14.pdf
  • Vision-based traffic measurement system icpr04.pdf
  • commercial/
    • GridSmart.pdf
    • THE PROMETHEUS PROGRAMME 92.pdf
  • in_vehicle/
    • A System for Real-time Detection and Tracking of Vehicles from a Single Car-mounted Camera itsc112.pdf
    • Combining Monocular and Stereo-Vision for Real-Time Vehicle Ranging and Tracking on Multilane Highways itsc11.pdf
    • Vehicle detection and tracking in car video based on motion model itst11.pdf
  • semantic/
    • A real-time computer vision system for measuring traffic parameters cvpr97.pdf
    • Large Scale Automated Analysis of Vehicle Interactions and Collisions.pdf
    • Real-Time Video-Based Traffic Measurement and Visualization System for EnergyEmissions itst12.pdf
    • Video processing techniques for traffic information acquisition using uncontrolled video streams itsc09.pdf
  • survey/
    • A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos cviu14.pdf
    • A review of computer vision techniques for the analysis of urban traffic itst11.pdf
    • A survey of video processing techniques for traffic applications ivc03.pdf
    • A Survey of Vision-Based Traffic Monitoring of Road Intersections itst16.pdf
    • A survey on visual surveillance of object motion and behaviors tsmc04.pdf
    • Background subtraction for automated multisensor surveillance A comprehensive review eurasip jasp10.pdf
    • Looking at Vehicles on the Road A Survey of Vision-Based Vehicle Detection, Tracking, and Behavior Analysis itst13.pdf
    • On-Road Vehicle Detection Using Optical Sensors A Review pami06.pdf
    • Tracking all traffic computer vision algorithms for monitoring vehicles, individuals, and crowds iram05.pdf
    • Traffic Monitoring and Control Using Machine Vision A Survey TIE85.pdf
    • Traffic monitoring with computer vision sami09.pdf
    • Traffic Surveillance A Review of Vision Based Vehicle Detection, Recognition and Tracking ijaerv11n1_108.pdf
    • Video processing techniques for traffic flow monitoring A survey itsc11.pdf
  • uav/
    • 01570387.pdf
    • 05279483.pdf
    • 07090517.pdf
    • 07311600.pdf
    • 07546916.pdf
    • A pan-tilt camera fuzzy vision controller on an unmanned aerial vehicle iros09.pdf
    • Computer vision based general object following for gps-denied multirotor unmanned vehicles acc14.pdf
    • Efficient Road Detection and Tracking for Unmanned Aerial Vehicle itst16.pdf
    • Estimating speed profiles from aerial vision — A comparison of regression based sampling techniques med16.pdf
    • From images to traffic behavior - A UAV tracking and monitoring application icif07.pdf
    • Minimum Time UAV Pursuit of a Moving Ground Target Using Partial Information icuas15.pdf
    • Motion-vector clustering for traffic speed detection from UAV video isc216.pdf
    • Surveillance from above A detection-and-prediction based multiple target tracking method on aerial videos icns16.pdf
    • Vehicle detection methods from an unmanned aerial vehicle platform icves12.pdf
• unsorted/
  • Harmonization_SIG10.pdf
  • Harmonization_SIG10_supplementary.pdf
  • Phase-Based_Video.pdf
  • sun10.pdf
• video prediction/
  • VideoBERT A Joint Model for Video and Language Representation Learning 1904.01766v2 iccv19.pdf
• video_captioning/
  • Accurate and Fast Compressed Video Captioning iccv23.pdf
  • Delving Deeper into the Decoder for Video Captioning 2001.05614 ecai20.pdf
  • Describing Videos by Exploiting Temporal Structure 1502.08029 iccv15.pdf
  • Grounded Video Description 1812.06587 cvpr19.pdf
  • Learning to Compose Topic-Aware Mixture of Experts for Zero-Shot Video Captioning 1811.02765 aaai19 dummy code.pdf
  • Learning to Generate Grounded Visual Captions without Localization Supervision 1906.00283 eccv20.pdf
  • Long-term Recurrent Convolutional Networks for Visual Recognition and Description 1411.4389 cvpr15 tpami1704.pdf
  • MART Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning 2005.05402 acl20.pdf
  • Motion Words for Videos eccv14.pdf
  • Sequence to sequence video to text iccv15.pdf
  • Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning 1902.10322 cvpr19.pdf
  • SwinBERT End-to-End Transformers with Sparse Attention for Video Captioning cvpr22 microsoft 2111.13196.pdf
  • Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning 1905.01077v1 aaai19.pdf
  • Temporal Segment Captioning Network proj.pdf
  • Towards Automatic Learning of Procedures from Web Instructional Videos 1703.09788 aaai18.pdf
  • Translating Videos to Natural Language Using Deep Recurrent Neural Networks 1412.4729 naacl15.pdf
  • TVR A Large-Scale Dataset for Video-Subtitle Moment Retrieval 2001.09099.pdf
  • DVC/
    • A Better Use of Audio-Visual Cues Dense Video Captioning with Bi-modal Transformer 2005.08271.pdf
    • Bidirectional Attentive Fusion with Context Gating for Dense Video Captioning 1804.00100 cvpr18.pdf
    • Dense-Captioning Events in Videos 1705.00754 iccv17.pdf
    • End-to-End Dense Video Captioning with Masked Transformer 1804.00819 cvpr18.pdf
    • End-to-End Dense Video Captioning with Parallel Decoding cvpr21.pdf
    • Multi-modal Dense Video Captioning 2003.07758 cvprw20.pdf
    • Vid2Seq Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning cvpr23.pdf
    • Vid2Seq supplemental.pdf
    • Weakly Supervised Dense Video Captioning 1704.01502 cvpr17.pdf
  • grounding/
    • Grounded Video Description cvpr19.pdf
    • Grounding Visual Explanations ECCV18.pdf
    • Joint Event Detection and Description in Continuous Video Streams 1802.10250v3 wacv19.pdf
    • Spatio-Temporal Attention Models for Grounded Video Captioning 1610.04997 accv16.pdf
    • Video Object Grounding using Semantic Roles in Language Description 2003.10606 cvpr20.pdf
    • Visual Grounding via Accumulated Attention cvpr18.pdf
    • Weakly-Supervised Video Object Grounding from Text by Loss Weighting and Object Interaction bmvc18.pdf
  • review/
    • Video Description A Survey of Methods, Datasets, and Evaluation Metrics 1806.00186 acmcs1910.pdf
    • Video Description A Survey of Methods, Datasets, and Evaluation Metrics acm2011.pdf
• video_detection/
  • Deep Learning-based Multiple Pedestrians Detection-Tracking Framework HCIK16_ACM.pdf
  • Improving a real-time object detector with compact temporal information iccvw17.pdf
  • MODNet Moving Object Detection Network with Motion and Appearance for Autonomous Driving ax1711.pdf
  • Moving object detection in videos using principal component pursuit and convolutional neural networks globalsip1711.pdf
  • Object Detection from Video Sequences Using Deep Learning An Overview AISC1710_SPRINGER.pdf
  • Object recognition and detection with deep learning for autonomous driving applications sage_1706.pdf
  • Object Tracking in Video with TensorFlow msc_thes1610.pdf
  • Optimizing Video Object Detection via a Scale-Time Lattice_cvpr18.pdf
  • Seq-NMS for Video Object Detection ax1608.pdf
  • Video Object Detection for Tractability with Deep Learning Method CBD17.pdf
  • action/
    • Does Computer Vision Matter for Action 1905.12887.pdf
    • Learning Spatiotemporal Attention for Egocentric Action Recognition iccvw19.pdf
    • LSTA Long Short-Term Attention for Egocentric Action Recognition 1811.10698.pdf
    • Recurrent Tubelet Proposal and Recognition Networks for Action Detection eccv18.pdf
    • Tube Convolutional Neural Network (T-CNN) for Action Detection in Videos ax1708.pdf
    • Two-stream convolutional networks for action recognition in videos nips14.pdf
  • efficient/
    • NoScope Optimizing Neural Network Queries over Video at Scale ax1708 vldb17.pdf
  • fgfa/
    • Deep Feature Flow For Video Recognition cvpr17.pdf
    • Flow-Guided Feature Aggregation for Video Object Detection ax1708 iccv17.pdf
    • Towards High Performance Video Object Detection ax171130 cvpr18 microsoft.pdf
    • Towards High Performance Video Object Detection for Mobiles ax180416 microsoft.pdf
  • motion/
    • Event-based Moving Object Detection and Tracking ax1803.04523.pdf
    • MODNet Moving Object Detection Network 1709.04821 itsc18.pdf
    • Online Illumination Invariant Moving Object Detection by Generative Neural Network ax1808.01066.pdf
    • moving_camera/
      • An effective motion object detection method using optical flow estimation under a moving camera jvcir1808.pdf
      • Automatic Object Detection In Video Sequences With Camera In Motion (2004).pdf
      • Dense optical flow in stabilized scenes for moving object detection from a moving camera iccas16.pdf
      • Detection of moving objects with a moving camera using non-panoramic background model mva1307_sl.pdf
      • Detection of Moving Objects with Non-stationary Cameras in 5.8ms Bringing Motion Detection to Your Mobile Device cvprw13.pdf
      • Moving Object Detection With a Freely Moving Camera via Background Motion Subtraction tcsvt1702.pdf
      • Moving-object detection method for moving cameras by merging background subtraction and optical flow methods globalsip17.pdf
      • New trends on moving object detection in video images captured by a moving camera A survey cs_review_1805.pdf
      • Object-Level Motion Detection From Moving Cameras tcsvt17.pdf
      • Optical Flow Based Background Subtraction with a Moving Camera Application to Autonomous Driving ax1811.06660.pdf
      • Robust Moving Object Detection at Distance in the Visible Spectrum and Beyond Using A Moving Camera cvprw06.pdf
  • notes/
    • Context Matters Refining Object Detection in Video with Recurrent Neural Networks bmvc16.pdf
    • Flow-Guided Feature Aggregation for Video Object Detection ax1708 iccv17.pdf
    • Object_Detection_from_Video_Tubelets_with_Convolutional_Neural_Networks_CVPR16.pdf
    • Object_Detection_in_Videos_with_Tubelet_Proposal_Networks_ax1704_cvpr17.pdf
    • Online Video Object Detection using Association LSTM iccv17.pdf
  • proposals/
    • 4D Generic Video Object Proposals ax1901.09260.pdf
    • Adaptive video object proposals by a context-aware model mta18_spr.pdf
    • Detecting temporally consistent objects in videos through object class label propagation. wacv16.pdf
    • Spatio- temporal object detection proposals eccv14.pdf
    • Track and Segment An Iterative Unsupervised Approach for Video Object Proposals cvpr2016.pdf
    • Track and Segment An Iterative Unsupervised Approach for Video Object Proposals cvpr2016_supp.pdf
    • Video object proposals cvprw12.pdf
  • rnn/
    • A One-stage Temporal Detector with Attentional LSTM for Video Object Detection 2021.pdf
    • Context Matters Refining Object Detection in Video with Recurrent Neural Networks bmvc16.pdf
    • Looking Fast and Slow Memory-Guided Mobile Video Object Detection ax1903.10172.pdf
    • Mobile Video Object Detection with Temporally-Aware Feature Maps cvpr18.pdf
    • Online Video Object Detection using Association LSTM iccv17.pdf
    • Recurrent neural networks for object detection in video sequences msc_thes170321.pdf
    • Temporally Identity-Aware SSD with Attentional LSTM 1803.00197.pdf
  • tubelets/
    • Object_Detection_from_Video_Tubelets_with_Convolutional_Neural_Networks_CVPR16.pdf
    • Object_Detection_in_Videos_with_Tubelet_Proposal_Networks_ax1704_cvpr17.pdf
    • T-CNN Tubelets with Convolutional Neural Networks for Object Detection from Videos ax1708 tcsvt.pdf
• video_segmentation/
  • A Video Representation Using Temporal Superpixels cvpr13.pdf
  • BoLTVOS Box-Level Tracking for Video Object Segmentation 1904.04552.pdf
  • CDTS Collaborative Detection, Tracking, and Segmentation for Online Multiple Object Segmentation in Videos_iccv17.pdf
  • DEEP CONVOLUTIONAL NEURAL NETWORKS FOR SEMANTIC VIDEO OBJECT SEGMENTATION mscthes16.pdf
  • End-to-end Learning of Driving Models from Large-scale Video Datasets arxiv16_12.pdf
  • End-to-End Video Instance Segmentation with Transformers cvpr21.pdf
  • Ensemble Video Object Cut in Highly Dynamic Scenes cvpr13.pdf
  • Fast and Accurate Online Video Object Segmentation via Tracking Parts 1806.02323 cvpr18.pdf
  • Improving Semantic Segmentation via Video Prediction and Label Relaxation ax1812.01593 cvpr19.pdf
  • Instance Segmentation and Tracking with Cosine Embeddings and Recurrent Hourglass Networks 1806.02070 miccai08.pdf
  • Learning Video Object Segmentation from Static Images cvpr17 masktrack.pdf
  • Learning What to Learn for Video Object Segmentation ax2003.11540.pdf
  • Motion trajectory segmentation via minimum cost multicuts iccv15.pdf
  • Online Adaptation of Convolutional Neural Networks for Video Object Segmentation ax1708 bmvc17.pdf
  • Online Video Object Segmentation via Convolutional Trident Network cvpr17.pdf
  • Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks ax1708 iccv17.pdf
  • PReMVOS Proposal-generation, Refinement and Merging for Video Object Segmentation accv18.pdf
  • Video Instance Segmentation 1905.04804 iccv19.pdf
  • Video Object Segmentation Without Temporal Information ax1709.06031 tpami18.pdf
  • 617/
    • Efficient Hierarchical Graph Based Video Segmentation cvpr10.pdf
    • Foreground Segmentation Using a Triplet Convolutional Neural Network for Multiscale Feature Encoding ax1801.pdf
    • FusionSeg Learning to combine motion and appearance for fully automatic segmentation of generic objects in videos cvpr2017.pdf
    • MaskRNN Instance Level Video Object Segmentation nips17.pdf
    • OSVOS One-Shot Video Object Segmentation ax1704 cvpr17.pdf
    • Unsupervised Learning of Video Representations using LSTMs ax15.pdf
    • Unsupervised Learning of Visual Representations using Videos ax15.pdf
    • Unsupervised object segmentation in video by efficient selection of highly probable positive features ax170419.pdf
    • Unsupervised Video Segmentation via Spatio-Temporally Nonlocal Appearance Learning ax1612.pdf
    • Video Segmentation by Non-Local Consensus Voting bmvc14.pdf
    • Video Segmentation via Object Flow cvpr16.pdf
  • davis_2017/
    • Instance Re-Identification Flow for Video Object Segmentation DAVIS-Challenge-3rd-Team.pdf
    • Learning to Segment Instances in Videos with Spatial Propagation Network cvprw17DAVIS-Challenge-6th-Team.pdf
    • Lucid Data Dreaming for Object Tracking cvprw17 DAVIS-Challenge-2nd-Team.pdf
    • Multiple-Instance Video Segmentation with Sequence-Specific Object Proposals cvprw17DAVIS-Challenge-4th-Team.pdf
    • One-Shot Video Object Segmentation with Iterative Online Fine-Tuning cvprw17DAVIS-Challenge-8th-Team.pdf
    • Online Adaptation of Convolutional Neural Networks for the 2017 DAVIS Challenge cvprw17 DAVIS-Challenge-5th-Team.pdf
    • Some Promising Ideas about Multi-instance Video Segmentation cvprw17DAVIS-Challenge-7th-Team.pdf
    • Video Object Segmentation using Tracked Object Proposals cvprw17 DAVIS-Challenge-9th-Team.pdf
    • Video Object Segmentation with Re-identification cvprw17 DAVIS-Challenge-1st-Team.pdf
  • instance/
    • IDOL In Defense of Online Models for Video Instance Segmentation 2207.10661 eccv22.pdf
    • SeqFormer Sequential Transformer for Video Instance Segmentation 2112.08275 eccv22.pdf
    • VITA Video Instance Segmentation via Object Token Association 2206.04403.pdf
  • menna/
    • RTSEG REAL-TIME SEMANTIC SEGMENTATION COMPARATIVE STUDY ax1803.02758 icip18.pdf
    • ShuffleSeg Real-time Semantic Segmentation Network ax1803.03816.pdf
    • Video Segmentation using Teacher Student Adaptation in HRI ax1810.07733.pdf
  • motion/
    • Coherent Motion Segmentation in Moving Camera Videos Using Optical Flow Orientations iccv13.pdf
    • Learning to Segment Moving Objects in Videos ax1505 cvpr15.pdf
    • Segmentation of Moving Objects by Long Term Video Analysis tpami14.pdf
  • panoptic/
    • A Generalist Framework for Panoptic Segmentation of Images and Videos iccv23 2210.06366.pdf
• video_synthesis/
  • Deep multi-scale video prediction beyond mean square error ax1602 iclr16.pdf