AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

Pengxu Wei, Sun Yat-Sen University
Hannan Lu, Harbin Institute of Technology
Radu Timofte, ETH Zürich
Liang Lin, Sun Yat-Sen University
Wangmeng Zuo, Harbin Institute of Technology
Zhihong Pan, Baidu, Inc.
Baopu Li, Baidu, Inc.
Teng Xi


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.