Hernandez-Juarez et al. propose a Bayesian framework to improve the generalization performance to new devices via a multi-hypothesis strategy (CVPR2020). Firstly, a set of candidate scene illuminants are selected in a data-driven fashion and applied to a target image to generate a set of corrected images. Secondly, for each corrected image, the likelihood of the light source being achromatic is estimated using a camera-agnostic CNN. Finally, the proposed method explicitly learns a final illumination estimate from the generated posterior probability distribution.

You can access the paper using this link and the code is also publicly available.