论文标题
AIM 2020：场景重新定论和照明估计挑战
AIM 2020: Scene Relighting and Illumination Estimation Challenge
论文作者
论文摘要
我们回顾了针对虚拟图像重新定义和照明估算的目标2020挑战。本文介绍了在挑战中使用的新型VIDIT数据集以及在3个挑战赛中的不同提议的解决方案和最终评估结果。第一轨被认为是一对一的重新贴；目的是要重新获得具有不同色温和照明方向的场景的输入照片（即光源位置）。第二轨的目的是从给定的图像估计照明设置，即色温和方向。最后，第三首曲目处理了任何一对一的重新，因此对第一条曲目进行了概括。目标色温和方向而不是预先确定，而是由指南图像给出。参与者被允许使用其轨道第1和2个解决方案的轨道解决方案。轨道分别有94、52和56名注册参与者，导致了最后的比赛阶段确认了20次确认的提交。
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.
