Zhongyun Hu

TL;DR: The AIM 2020 challenge on virtual image relighting and illumination estimation as discussed by the authors focused on one-to-one relighting, where the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation.

TL;DR: The NTIRE 2021 depth guided image relighting challenge as mentioned in this paper focused on one-to-one relighting where the goal is to transform the illumination setup of an input image (color temperature and light source position) to the target illumination setup.

TL;DR: The novel VIDIT dataset used in the AIM 2020 challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks are presented.

TL;DR: Li et al. as mentioned in this paper proposed a self-attention auto-encoder for any-to-any relighting, which adopted an implicit scene representation learned by the encoder to render the relit image using the decoder based on the learned scene representation.

TL;DR: PNRNet is presented, a novel neural architecture that decomposes the any-to-any relighting task into three simpler sub-tasks, i.e. lighting estimation, color temperature transfer, and lighting direction transfer, to avoid the task-aliasing effects.