In this paper, we provide a novel dataset designed for camera invariant color constancy
research. Camera invariance corresponds to the robustness of an algorithm's performance …

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 …

Implementing color constancy as a pre-processing step in contemporary digital cameras is
of significant importance as it removes the influence of scene illumination on object colors …

Achieving color constancy is an important part of image preprocessing pipeline of
contemporary digital cameras. Its goal is to eliminate the influence of the illumination color …

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 …

Most digital camera pipelines use color constancy methods to reduce the influence of
illumination and camera sensor on the colors of scene objects. The highest accuracy of color …

Color constancy benchmarks are mostly created by using cameras with similar hardware
and by capturing the scenes under similar illuminants. Therefore, ground truth information is …

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

Color constancy is still one of the biggest challenges in camera color processing.
Convolutional neural networks have been able to improve the situation but there are still …

Color Constancy aims to correct image color casts caused by scene illumination. Recently,
although the deep learning approaches have remarkably improved on single-camera data …