… Fourier color constancy” (FFCC) [9], but embeds them in a multi-input hypernetwork to enable
accurate cross-camera … Here, we present a convolutional color constancy model that is a …

… convolutional neural network without pre-trained layers, that achieves state-of-the-art results.
The model contains five convolutional … Cross camera experiments were also performed and …

… and compare it with other color constancy augmentation techniques used in the literature. …
We also show the results of other camera-specific color constancy methods reported in past …

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 dual-…

… Computational color constancy aims to adjust the colors in an image to how they would
appear under a canonical illuminant, which is achieved by removing the color cast of the …

… Transfer Learning Color Constancy (TLCC) method that leverages cross-camera RAW data
… Recently, many learning-based color constancy methods based on the convolutional neural …

… In this section, we first briefly discuss two color constancy works related to CISS: the
camera-independent learning-based methods and … Cross-camera convolutional color constancy …

… color constancy algorithms, some illuminants are neglected. In this study, we introduce a
largescale synthetic color constancy … having values away from the color temperature curve. To …

Background In computer vision, there are multiple calibration problems. The most fundamental
one is the camera calibration, which determines the intrinsic and extrinsic parameters of a …

… color (LSR-color) image. We propose a cross-camera synthesis (CCS) module to learn
and transfer illumination, color, and resolution attributes across paired HSR-mono and LSR-…