Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.
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Updated
Jul 5, 2023 - Python
Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.
White balance camera-rendered sRGB images (CVPR 2019) [Matlab & Python]
WB color augmenter improves the accuracy of image classification and image semantic segmentation methods by emulating different WB effects (ICCV 2019) [Python & Matlab].
Reference code for the paper "Cross-Camera Convolutional Color Constancy" (ICCV 2021)
Reference code for the paper Auto White-Balance Correction for Mixed-Illuminant Scenes.
[CVPR2020] A Multi-Hypothesis Approach to Color Constancy
An official TensorFlow implementation of “CLCC: Contrastive Learning for Color Constancy” accepted at CVPR 2021.
Cube++ is a novel dataset collected for illumination estimation problem. It has 4890 raw 18-megapixel images, each containing a SpyderCube color target in their scenes, manually labelled categories, and ground truth illumination chromaticities.
Fully supervised binary classification of skin lesions from dermatoscopic images using an ensemble of diverse CNN architectures (EfficientNet-B6, Inception-V3, SEResNeXt-101, SENet-154, DenseNet-169) with multi-scale input.
C++ Automated white balance using lodepng and some color correction
Implementation of the method described in the paper "Quasi-unsupervised color constancy" - CVPR 2019
Semantic information can help CNNs to get better illuminant estimation -- a proof of concept
Sensor-Independent Illumination Estimation for DNN Models (BMVC 2019)
Reference code for the paper Interactive White Balancing for Camera-Rendered Images Mahmoud Afifi and Michael S. Brown. In Color and Imaging Conference (CIC), 2020.
Matlab Implementation of VISSAP 2019 <<Revisiting Gray Pixel for Statistical Illumination Estimation>>
Bias correction method for illuminant estimation -- JOSA 2019
A suite of tests to assess attention faithfulness for explainability
Code for "Truncated Edge-based Color Constancy"
Official codes for 'Domain Adversarial Learning for Color Constancy'
Source code and dataset for the paper titled "Colour alignment for relative colour constancy via non-standard references"
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