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 …

For decades, photographs have been used to document space-time events and they have
often served as evidence in courts. Although photographers are able to create composites of …

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 …

Color constancy is the problem of inferring the color of the light that illuminated a scene,
usually so that the illumination color can be removed. Because this problem is …

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 …

Image colors are biased by the color of the prevaling illumination. As such the color at pixel
cannot always be used directly in solving vision tasks from recognition, to tracking to general …

Auto white balance (AWB) is applied by camera hardware at capture time to remove the
color cast caused by the scene illumination. The vast majority of white-balance algorithms …

Most existing color constancy algorithms assume uniform illumination. However, in real-
world scenes, this is not often the case. Thus, we propose a novel framework for estimating …

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. Non-uniform …

The aim of computational color constancy is to estimate the actual surface color in an
acquired scene disregarding its illuminant. Many solutions try to first estimate the illuminant …