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Get Free AccessThis paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Taking the three main aspects (i.e., number of parameters, inference/running time, fidelity (PSNR)) of MSRResNet as the baseline, Track 1 aims to reduce the amount of parameters while being constrained to maintain or improve the running time and the PSNR result, Tracks 2 and 3 aim to optimize running time and PSNR result with constrain of the other two aspects, respectively. Each track had an average of 64 registered participants, and 12 teams submitted the final results. They gauge the state-of-the-art in single image super-resolution.
Kai Zhang, Shuhang Gu, Radu Timofte, Hui Zheng, Xinbo Gao, Dongliang Xiong, Shuai Liu, Ruipeng Gang, Nan Nan, Chenghua Li, Xueyi Zou, Ning Kang, Zhan Wang, Hang Xu, Chaofeng Wang, Zheng Li, Linlin Wang, Jun Shi, Wenyu Sun, Zhiqiang Lang, Jiangtao Nie, Wei Wei, Lei Zhang, Yazhe Niu, Peijin Zhuo, Xiangzhen Kong, Long Sun, Wenhao Wang (2019). AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results. , DOI: https://doi.org/10.1109/iccvw.2019.00441.
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Type
Preprint
Year
2019
Authors
28
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1109/iccvw.2019.00441
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