Cascading Convolutional Color Constancy (AAAI 2020)

Yu et al. introduce a novel algorithm by Cascading Convolutional Color Constancy (in short, C4) to improve the robustness of regression learning and achieve stable generalization capability across datasets (different cameras and scenes) in a unique framework.  The proposed C4 method ensembles a series of dependent illumination hypotheses from each cascade stage via introducing a weighted multiply-accumulate loss function, which can inherently capture different modes of illuminations and explicitly enforce coarse-to-fine network optimization.

The paper can be accessed here, with the publicly available code present here.