Color constancy is one of the important research areas with a wide range of applications in
the fields of color image processing and computer vision. One such application is video …

Prediction on complex time series has received much attention during the last decade. This
paper reviews least square and radial basis function based predictors and proposes a …

Improvements in color constancy have arisen from the use of convolutional neural networks
(CNNs). However, the patch-based CNNs that exist for this problem are faced with the issue …

Computational color constancy is a fundamental prerequisite for many computer vision
applications. This paper presents a survey of many recent developments and state-of-the-art …

In this work we describe a Convolutional Neural Network (CNN) to accurately predict the
scene illumination. Taking image patches as input, the CNN works in the spatial domain …

Abstract 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. By …

Illuminant estimation to achieve color constancy is an ill-posed problem. Searching the large
hypothesis space for an accurate illuminant estimation is hard due to the ambiguities of …

In this paper, we present a three-stage method for the estimation of the color of the illuminant
in RAW images. The first stage uses a convolutional neural network that has been specially …

In this paper, we present CLCC, a novel contrastive learning framework for color constancy.
Contrastive learning has been applied for learning high-quality visual representations for …

Illumination estimation is the process of determining the chromaticity of the illumination in an
imaged scene in order to remove undesirable color casts through white-balancing. While …