UDC 2020挑战在显示下摄像机的图像恢复：方法和结果

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UDC 2020挑战在显示下摄像机的图像恢复：方法和结果

UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results

论文作者

Zhou, Yuqian, Kwan, Michael, Tolentino, Kyle, Emerton, Neil, Lim, Sehoon, Large, Tim, Fu, Lijiang, Pan, Zhihong, Li, Baopu, Yang, Qirui, Liu, Yihao, Tang, Jigang, Ku, Tao, Ma, Shibin, Hu, Bingnan, Wang, Jiarong, Puthussery, Densen, S, Hrishikesh P, Kuriakose, Melvin, C V, Jiji, Sundar, Varun, Hegde, Sumanth, Kothandaraman, Divya, Mitra, Kaushik, Jassal, Akashdeep, Shah, Nisarg A., Nathan, Sabari, Rahel, Nagat Abdalla Esiad, Chen, Dafan, Nie, Shichao, Yin, Shuting, Ma, Chengconghui, Wang, Haoran, Zhao, Tongtong, Zhao, Shanshan, Rego, Joshua, Chen, Huaijin, Li, Shuai, Hu, Zhenhua, Lau, Kin Wai, Po, Lai-Man, Yu, Dahai, Rehman, Yasar Abbas Ur, Li, Yiqun, Xing, Lianping

论文摘要

本文是第一张播放摄像机（UDC）图像修复挑战的报告与ECCV 2020的RLQ研讨会结合使用。挑战是基于新收集的分散摄像机的数据库。挑战轨道对应于两种类型的显示：4K透明的OLED（T-OLED）和手机Pentile OLED（P-OLED）。除了大约150支球队进行了挑战，有8个和9个团队在每个赛道的测试阶段提交了结果。本文中的结果是隔离摄像头修复的最新恢复性能。数据集和纸张可在https://yzhouas.github.io/projects/udc/udc.html上找到。

This paper is the report of the first Under-Display Camera (UDC) image restoration challenge in conjunction with the RLQ workshop at ECCV 2020. The challenge is based on a newly-collected database of Under-Display Camera. The challenge tracks correspond to two types of display: a 4k Transparent OLED (T-OLED) and a phone Pentile OLED (P-OLED). Along with about 150 teams registered the challenge, eight and nine teams submitted the results during the testing phase for each track. The results in the paper are state-of-the-art restoration performance of Under-Display Camera Restoration. Datasets and paper are available at https://yzhouas.github.io/projects/UDC/udc.html.

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