Two new CNN-based color constancy works have recently appeared on arXiv by Laakom et. al. Color Constancy Convolutional Autoencoder studies the importance of pre-training for the generalization capability in the color constancy problem. Bag of Color Features For Color Constancy proposes a new approach called Bag of Color Features (BoCF), building upon Bag-of-Features pooling along with self attention mechanisms.
Generative Adversarial Networks (GANs) have demonstrated remarkable results on many image-to-image translation problems. In that sense, Das et al. formulate the color constancy task as an image-to-image translation problem using GANs. By conducting a large set of experiments on different datasets, they provide an experimental survey on the use of different types of GANs to solve for color constancy i.e. CC-GANs (Color Constancy GANs).