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 …

The capability of learning and generalizing from very few samples successfully is a
noticeable demarcation separating artificial intelligence and human intelligence. Despite the …

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 …

Deep neural networks (DNNs) have been widely used for illuminant estimation, which
commonly requires great efforts to collect sensor-specific data. In this paper, we propose a …

Color constancy aims to restore the constant colors of a scene under different illuminants.
However, due to the existence of camera spectral sensitivity, the network trained on a certain …

In the main paper, we used a histogram bin size of 64 (ie, n= 64) with a histogram bin width
ϵ=(bmax− bmin)/n, where bmax and bmin are the histogram boundary values. In our …