Color Constancy
30 papers with code • 0 benchmarks • 5 datasets
Color Constancy is the ability of the human vision system to perceive the colors of the objects in the scene largely invariant to the color of the light source. The task of computational Color Constancy is to estimate the scene illumination and then perform the chromatic adaptation in order to remove the influence of the illumination color on the colors of the objects in the scene.
Benchmarks
These leaderboards are used to track progress in Color Constancy
Most implemented papers
A Benchmark for Temporal Color Constancy
The conventional approach is to use a single frame - shot frame - to estimate the scene illumination color.
Fast Fourier Color Constancy
We present Fast Fourier Color Constancy (FFCC), a color constancy algorithm which solves illuminant estimation by reducing it to a spatial localization task on a torus.
FC4: Fully Convolutional Color Constancy With Confidence-Weighted Pooling
However, the patch-based CNNs that exist for this problem are faced with the issue of estimation ambiguity, where a patch may contain insufficient information to establish a unique or even a limited possible range of illumination colors.
Semantic White Balance: Semantic Color Constancy Using Convolutional Neural Network
The goal of computational color constancy is to preserve the perceptive colors of objects under different lighting conditions by removing the effect of color casts caused by the scene's illumination.
Revisiting Gray Pixel for Statistical Illumination Estimation
We present a statistical color constancy method that relies on novel gray pixel detection and mean shift clustering.
Color Constancy by Reweighting Image Feature Maps
In this study, a novel illuminant color estimation framework is proposed for computational color constancy, which incorporates the high representational capacity of deep-learning-based models and the great interpretability of assumption-based models.
Decoupling Semantic Context and Color Correlation with multi-class cross branch regularization
This paper presents a novel design methodology for architecting a light-weight and faster DNN architecture for vision applications.
Conditional GANs for Multi-Illuminant Color Constancy: Revolution or Yet Another Approach?
Non-uniform and multi-illuminant color constancy are important tasks, the solution of which will allow to discard information about lighting conditions in the image.
Artificial Color Constancy via GoogLeNet with Angular Loss Function
Color Constancy is the ability of the human visual system to perceive colors unchanged independently of the illumination.
The Visual Centrifuge: Model-Free Layered Video Representations
True video understanding requires making sense of non-lambertian scenes where the color of light arriving at the camera sensor encodes information about not just the last object it collided with, but about multiple mediums -- colored windows, dirty mirrors, smoke or rain.