The purpose of color constancy algorithm is to eliminate the influence of illumination on the
color of objects in the scene, so that the computer has the same color constancy ability as …

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 order to fully extract the illumination information, this work proposes a color constancy
algorithm based on Swin Transformer. The algorithm calculates the self attention by taking …

Deep learning methods have achieved a large step forward in many computer vision
applications. With mechanisms such as attention, deep models can now guide themselves …

Color constancy refers to the ability to make the color of an object not change with the
change of the light color of the scene. The use of convolutional neural networks improves …

Traditional methods of color constancy have solved the problem by modeling the statistical
laws of natural objects and illumination colors. With the development of convolutional neural …

A learning-based multibranch deep probability network is proposed to estimate the
illuminated color of the light source in a scene, commonly referred to as color constancy. The …

Computational colour constancy refers to the problem of obtaining reliable illuminant colour
so that the image can be rectified to generate a new image under the canonical illumination …

Computational color constancy refers to the problem of computing the illuminant color so
that the images of a scene under varying illumination can be normalized to an image under …

In this work, we constructed an improved vgg-16 convolutional neural network model for
color constancy, which we called VGGC network structure, to accurately predict scene …