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AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results (2009.06943v1)

Published 15 Sep 2020 in eess.IV and cs.CV

Abstract: This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor x4 based on a set of prior examples of low and corresponding high resolution images. The goal is to devise a network that reduces one or several aspects such as runtime, parameter count, FLOPs, activations, and memory consumption while at least maintaining PSNR of MSRResNet. The track had 150 registered participants, and 25 teams submitted the final results. They gauge the state-of-the-art in efficient single image super-resolution.

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Authors (78)
  1. Kai Zhang (542 papers)
  2. Martin Danelljan (96 papers)
  3. Yawei Li (72 papers)
  4. Radu Timofte (299 papers)
  5. Jie Liu (492 papers)
  6. Jie Tang (302 papers)
  7. Gangshan Wu (70 papers)
  8. Yu Zhu (123 papers)
  9. Xiangyu He (19 papers)
  10. Wenjie Xu (29 papers)
  11. Chenghua Li (14 papers)
  12. Cong Leng (13 papers)
  13. Jian Cheng (127 papers)
  14. Guangyang Wu (8 papers)
  15. Wenyi Wang (35 papers)
  16. Xiaohong Liu (117 papers)
  17. Hengyuan Zhao (10 papers)
  18. Xiangtao Kong (13 papers)
  19. Jingwen He (22 papers)
  20. Yu Qiao (563 papers)
Citations (84)

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