AIM 2020: Scene Relighting and Illumination Estimation Challenge
원문 초록
We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks. The first track considered one-to-one relighting; the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation (i.e., light source position). The goal of the second track was to estimate illumination settings, namely the color temperature and orientation, from a given image. Lastly, the third track dealt with any-to-any relighting, thus a generalization of the first track. The target color temperature and orientation, rather than being pre-determined, are instead given by a guide image. Participants were allowed to make use of their track 1 and 2 solutions for track 3. The tracks had 94, 52, and 56 registered participants, respectively, leading to 20 confirmed submissions in the final competition stage.
함께 살펴볼 논문
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DNF-Avatar: Distilling Neural Fields for Real-time Animatable Avatar Relighting
LBM: Latent Bridge Matching for Fast Image-to-Image Translation
Light-A-Video: Training-free Video Relighting via Progressive Light Fusion
All-frequency Full-body Human Image Relighting
Nighttime Person Re-Identification via Collaborative Enhancement Network with Multi-domain Learning
Intrinsic Harmonization for Illumination-Aware Compositing
토론
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