… propose to use CNNs to learn feature hierarchies to achieve robust color constancy. A deep
CNN model is used consisting of eight (hidden) layers. Such a deep model will yield multi-…

… learning capability of the CNN, we trained a deep learning architecture for our own task: the
illumination estimation. We propose a deep learning based color constancy … color constancy …

… in the role of computational color constancy, which makes up the white-balance (WB)
routine on digital cameras. We focus on computational color constancy because it represents a …

… face learning … color constancy method that uses a multi-stream deep neural network (MSDNN)based
convoluted mixture of deep experts (CMoDE) fusion technique in performing deep …

… Together with learning an ad-hoc CNN for the color constancy problem, we also
investigate how a pre-trained one works on this problem. To this end, we extract a 4096-dimensional …

… Deep learning approaches to color constancy are limited by … to identify color in settings that
require color constancy, (2) to … for color constancy, and (3) to test whether human-like color …

… that features learned from deep neural networks are better than hand-crafted ones [39, 41,
50]. Consequently, deep learning based color constancy research has gradually received …

… the problem of temporal color constancy, relaxing the … (a novel recurrent deep net) for
temporal color constancy task. … as two modalities of deep learning. CNNs have achieved …

… Contemporary approaches frame the color constancy problem as learning camera specific
… We propose a Bayesian framework that naturally handles color constancy ambiguity via a …

… color constancy. The method proposed in this paper relates to the computer vision color
constancy… Motivated by the success of deep learning approaches in many computer vision tasks, …