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arxiv: 2104.10781 · v6 · pith:KYTOOFDHnew · submitted 2021-04-21 · 📡 eess.IV · cs.CV

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

Ren Yang , Radu Timofte , Jing Liu , Yi Xu , Xinjian Zhang , Minyi Zhao , Shuigeng Zhou , Kelvin C.K. Chan
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Shangchen Zhou Xiangyu Xu Chen Change Loy Xin Li Fanglong Liu He Zheng Lielin Jiang Qi Zhang Dongliang He Fu Li Qingqing Dang Yibin Huang Matteo Maggioni Zhongqian Fu Shuai Xiao Cheng li Thomas Tanay Fenglong Song Wentao Chao Qiang Guo Yan Liu Jiang Li Xiaochao Qu Dewang Hou Jiayu Yang Lyn Jiang Di You Zhenyu Zhang Chong Mou Iaroslav Koshelev Pavel Ostyakov Andrey Somov Jia Hao Xueyi Zou Shijie Zhao Xiaopeng Sun Yiting Liao Yuanzhi Zhang Qing Wang Gen Zhan Mengxi Guo Junlin Li Ming Lu Zhan Ma Pablo Navarrete Michelini Hai Wang Yiyun Chen Jingyu Guo Liliang Zhang Wenming Yang Sijung Kim Syehoon Oh Yucong Wang Minjie Cai Wei Hao Kangdi Shi Liangyan Li Jun Chen Wei Gao Wang Liu Xiaoyu Zhang Linjie Zhou Sixin Lin Ru Wang
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classification 📡 eess.IV cs.CV
keywords challengequalitytrackscompressedenhancementvideoenhancingmethods
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This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results. In this challenge, the new Large-scale Diverse Video (LDV) dataset is employed. The challenge has three tracks. Tracks 1 and 2 aim at enhancing the videos compressed by HEVC at a fixed QP, while Track 3 is designed for enhancing the videos compressed by x265 at a fixed bit-rate. Besides, the quality enhancement of Tracks 1 and 3 targets at improving the fidelity (PSNR), and Track 2 targets at enhancing the perceptual quality. The three tracks totally attract 482 registrations. In the test phase, 12 teams, 8 teams and 11 teams submitted the final results of Tracks 1, 2 and 3, respectively. The proposed methods and solutions gauge the state-of-the-art of video quality enhancement. The homepage of the challenge: https://github.com/RenYang-home/NTIRE21_VEnh

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