[ICLR 2024] Controlling Vision-Language Models for Universal Image Restoration. 5th place in the NTIRE 2024 Restore Any Image Model in the Wild Challenge.

[AAAI 2020] Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN

Collection of recent shadow removal works, including papers, codes, datasets, and metrics.

[IJCNN 2023 Oral]: SpA-Former:An Effective and Lightweight Transformer for Image Shadow Removal

[ICCV2021]"DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised Domain-Classifier Guided Network", https://arxiv.org/abs/2207.10434

[ICCV 2023] A large-scale high-resolution dataset satisfies all important data features about document shadow, covers a large number of document shadow images.

We have used Deep Reinforcement Learning and Advanced Computer Vision techniques to for the creation of Smart Traffic Signals for Indian Roads. We have created the scripts for using SUMO as our environment for deploying all our RL models.

[AAAI 2022] The first dataset on foreground object shadow generation for image composition in real-world scenes. The code used in our paper "Shadow Generation for Composite Image in Real-world Scenes", AAAI2022. Useful for shadow generation, shadow removal, image composition, etc.

Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data | ICCV 2019

Direction-Aware Spatial Context Features for Shadow Detection and Removal | CVPR 2018 (Oral) & TPAMI 2019

ShadowFormer (AAAI2023), Pytorch implementation

Code for Blind Image Decomposition (BID) and Blind Image Decomposition network (BIDeN). ECCV, 2022.

Code for paper: Memory Augment is All Your Need for image restoration(cloud,rain,shadow removal, low-light image enhancement, image deblur)即插即用提点的记忆模块

Official implementation for ICCV19 "Shadow Removal via Shadow Image Decomposition"

Learning from Synthetic Shadows for Shadow Detection and Removal [Inoue and Yamasaki, IEEE TCSVT 2021].

Dataset and Code for our CVPR'18 paper ST-CGAN: "Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal"

Unofficial implementation of ''Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal'' with PyTorch

Various models for handling underexposure, overexposure, super-resolution, shadow removal, etc.

A Survey on Image and Video Shadow Detection, Removal, and Generation in the Era of Deep Learning (Awesome & Benchmark)

Unofficial implementation of ''BEDSR-Net: A Deep Shadow Removal from a Single Document Image'' with PyTorch