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arxiv: 2008.07742 · v1 · pith:RDSHYOUD · submitted 2020-08-18 · eess.IV · cs.CV

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

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