Matlab Implementation of VISSAP 2019 <<Revisiting Gray Pixel for Statistical Illumination Estimation>>
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Updated
Feb 20, 2019 - MATLAB
Matlab Implementation of VISSAP 2019 <<Revisiting Gray Pixel for Statistical Illumination Estimation>>
Image processing program to recognize resulting colors of biological assays
Learning Color Constancy Using Convolutional Neural Networks (ConvNets)
A new method for image enhancement in Matlab
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.
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.
Bias correction method for illuminant estimation -- JOSA 2019
[CVPR2020] A Multi-Hypothesis Approach to Color Constancy
An official TensorFlow implementation of “CLCC: Contrastive Learning for Color Constancy” accepted at CVPR 2021.
Not a serious implementation of Deep white balance in Tensorflow. Aimed for personal learning.
Source code and dataset for the paper titled "Colour alignment for relative colour constancy via non-standard references"
Code for "Truncated Edge-based Color Constancy"
Implementation of the method described in the paper "Quasi-unsupervised color constancy" - CVPR 2019
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].
Semantic information can help CNNs to get better illuminant estimation -- a proof of concept
Reference code for the paper Auto White-Balance Correction for Mixed-Illuminant Scenes.
Official codes for 'Domain Adversarial Learning for Color Constancy'
Sensor-Independent Illumination Estimation for DNN Models (BMVC 2019)
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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