AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results-Reference-Cited by-同舟云学术

AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results

Published:2020 Issue: Volume: Page:5-40
ISSN:0302-9743
Container-title:Computer Vision – ECCV 2020 Workshops
language:
Short-container-title:

Author:

Zhang Kai,Danelljan Martin,Li Yawei,Timofte Radu,Liu Jie,Tang Jie,Wu Gangshan,Zhu Yu,He Xiangyu,Xu Wenjie,Li Chenghua,Leng Cong,Cheng Jian,Wu Guangyang,Wang Wenyi,Liu Xiaohong,Zhao Hengyuan,Kong Xiangtao,He Jingwen,Qiao Yu,Dong Chao,Luo Xiaotong,Chen Liang,Zhang Jiangtao,Suin Maitreya,Purohit Kuldeep,Rajagopalan A. N.,Li Xiaochuan,Lang Zhiqiang,Nie Jiangtao,Wei Wei,Zhang Lei,Muqeet Abdul,Hwang Jiwon,Yang Subin,Kang JungHeum,Bae Sung-Ho,Kim Yongwoo,Qu Yanyun,Jeon Geun-Woo,Choi Jun-Ho,Kim Jun-Hyuk,Lee Jong-Seok,Marty Steven,Marty Eric,Xiong Dongliang,Chen Siang,Zha Lin,Jiang Jiande,Gao Xinbo,Lu Wen,Wang Haicheng,Bhaskara Vineeth,Levinshtein Alex,Tsogkas Stavros,Jepson Allan,Kong Xiangzhen,Zhao Tongtong,Zhao Shanshan,Hrishikesh P. S.,Puthussery Densen,Jiji C. V.,Nan Nan,Liu Shuai,Cai Jie,Meng Zibo,Ding Jiaming,Ho Chiu Man,Wang Xuehui,Yan Qiong,Zhao Yuzhi,Chen Long,Sun Long,Wang Wenhao,Liu Zhenbing,Lan Rushi,Umer Rao Muhammad,Micheloni Christian

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-67070-2_1

Reference66 articles.

1. Agustsson, E., Timofte, R.: NTIRE 2017 challenge on single image super-resolution: dataset and study. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, July 2017

2. Bahat, Y., Michaeli, T.: Explorable super resolution. In: IEEE Conference on Computer Vision and Pattern Recognition (2020)

3. Bell-Kligler, S., Shocher, A., Irani, M.: Blind super-resolution kernel estimation using an internal-GAN. In: Advances in Neural Information Processing Systems, pp. 284–293 (2019)

4. Cai, H., Gan, C., Han, S.: Once for all: Train one network and specialize it for efficient deployment. arXiv preprint arXiv:1908.09791 (2019)

5. Cai, Y., et al.: Learning delicate local representations for multi-person pose estimation. arXiv preprint arXiv:2003.04030 (2020)

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