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

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          Abstract

          This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with focus on proposed solutions 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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          Author and article information

          Journal
          21 April 2021
          Article
          2104.10781
          9b2a6d2f-caf3-495b-8246-02f9d4ec8819

          http://creativecommons.org/licenses/by-nc-nd/4.0/

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          Custom metadata
          eess.IV cs.CV

          Computer vision & Pattern recognition,Electrical engineering
          Computer vision & Pattern recognition, Electrical engineering

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