AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
09/25/2020 
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by Pengxu Wei, et al. ∙
HUAWEI Technologies Co., Ltd.
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NetEase, Inc.
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Los Alamos National Laboratory
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Microsoft
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Université Libre de Bruxelles
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ETH Zurich
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Harbin Institute of Technology
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Guangdong University of Technology
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IEEE
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Tencent QQ
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Hong Kong Polytechnic University
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inceptioniai.org
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Baidu, Inc.
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USTC
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NetEase, Inc
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SUN YAT-SEN UNIVERSITY
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7
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This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This challenge involves three tracks to super-resolve an input image for ×2, ×3 and ×4 scaling factors, respectively. The goal is to attract more attention to realistic image degradation for the SR task, which is much more complicated and challenging, and contributes to real-world image super-resolution applications. 452 participants were registered for three tracks in total, and 24 teams submitted their results. They gauge the state-of-the-art approaches for real image SR in terms of PSNR and SSIM.
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