Abstract We present" Cross-Camera Convolutional Color Constancy"(C5), a learning-based
method, trained on images from multiple cameras, that accurately estimates a scene's …

Contemporary approaches frame the color constancy problem as learning camera specific
illuminant mappings. While high accuracy can be achieved on camera specific data, these …

Regressing the illumination of a scene from the representations of object appearances is
popularly adopted in computational color constancy. However, it's still challenging due to …

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 …

In this paper, we study the importance of pretraining for the generalization capability in the
color constancy problem. We propose two novel approaches based on convolutional …

In this paper, we provide a novel data set designed for Camera-independent color
constancy research. Camera independence corresponds to the robustness of an algorithm's …

Color constancy is an important process in camera pipeline to remove the color bias of
captured image caused by scene illumination. Recently, significant improvements in color …

Images have an ever-increasing presence in our daily lives. This increases the need for
accurate and efficient image processing. One of the first processing steps in modern …

This paper focuses on correcting a camera image that has been improperly white-balanced.
This situation occurs when a camera's auto white balance fails or when the wrong manual …

It is an ill-posed problem to recover the true scene colors from a color biased image by
discounting the effects of scene illuminant and camera spectral sensitivity (CSS) at the same …