Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalization for domain adaptation, and also for data augmentation. It also has multiple direct uses for photo montage and aesthetic enhancement. In this paper, we review the NTIRE 2021 depth guided image relighting challenge. We rely on the VIDIT dataset for each of our two challenge tracks, including depth information. The first track is 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. In the second track, the any-to-any relighting challenge, the objective is to transform the illumination settings of the input image to match those of another guide image, similar to style transfer. In both tracks, participants were given depth information about the captured scenes. We had nearly 250 registered participants, leading to 18 confirmed team submissions in the final competition stage. The competitions, methods, and final results are presented in this paper.
翻译:图像光照正在因其各种应用而引起越来越多的兴趣。 从研究角度来说,图像光照可以被利用来进行域适应的图像正常化和数据增强。 图像光照也可以被利用来同时进行域适应的图像正常化和数据增强。 图像光照也有多个直接用途。 在本文中, 我们审查了 2021 年的NTIRE 深度引导图像点亮挑战。 我们依靠 VIDIT 数据集来应对我们两个挑战轨道中的每一个, 包括深度信息 。 第一个轨道是在一对一的光照上, 目标是将输入图像( 彩色温度和光源位置) 的光化设置转换为目标照明设置 。 在第二个轨道上, 任何光照亮的挑战, 目标是将输入图像的光化设置转换为与另一个指南图像相匹配, 类似风格传输 。 在两个轨道上, 参与者都获得了关于所捕捉到的场景的深度信息。 我们有近250名注册的参与者, 导致18个团队在最后竞争阶段被确认的提交材料。 竞赛、 和最终结果都载于本文中。