The target article is an attempt to make some progress on the problem of color realism. Are
objects colored? And what is the nature of the color properties? We defend the view that …

When the illumination on a scene changes, so do the visual signals elicited by that scene. In
spite of these changes, the objects within a scene tend to remain constant in their apparent …

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 …

A fundamental problem in computer vision is that of inferring the intrinsic, 3D structure of the
world from flat, 2D images of that world. Traditional methods for recovering scene properties …

Histopathology diagnosis is based on visual examination of the morphology of histological
sections under a microscope. With the increasing popularity of digital slide scanners …

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 …

The superficial appearance and color of food are the first parameters of quality evaluated by
consumers, and are thus critical factors for acceptance of the food item by the consumer …

Color constancy is the ability to measure colors of objects independent of the color of the
light source. A well-known color constancy method is based on the gray-world assumption …

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 …