NTIRE 2018 Challenge on Single Image Super-Resolution: Methods and Results

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Timofte, Radu / Gu, Shuhang / Wu, Jiqing / Van Gool, Luc / Zhang, Lei / Yang, Ming-Hsuan / Haris, Muhammad / Shakhnarovich, Greg / Ukita, Norimichi / Hu, Shijia / Bei, Yijie / Hui, Zheng / Jiang, Xiao / Gu, Yanan / Liu, Jie / Wang, Yifan / Perazzi, Federico / McWilliams, Brian / Sorkin-Hornung, Alexander / Sorkine-Hornung, Olga / Schroers, Christopher / Yu, Jiahui / Fan, Yuchen / Yang, Jianchao / Xu, Ning / Wang, Zhaowen / Wang, Xinchao / Huang, Thomas S. / Wang, Xintao / Yu, Ke / Hui, Tak-Wai / Dong, Chao / Lin, Liang / Loy, Chen Change / Park, Dongwon / Kim, Kwanyoung / Chun, Se Young / Zhang, Kai / Liu, Pengjv / Zuo, Wangmeng / Guo, Shi / Liu, Jiye / Xu, Jinchang / Liu, Yijiao / Xiong, Fengye / Dong, Yuan / Bai, Hongliang / Damian, Alexandru / Ravi, Nikhil / Menon, Sachit / Rudin, Cynthia / Seo, Junghoon / Jeon, Taegyun / Koo, Jamyoung / Jeon, Seunghyun / Kim, Soo Ye / Choi, Jae-Seok / Ki, Sehwan / Seo, Soomin / Sim, Hyeonjun / Kim, Saehun / Kim, Munchurlresearcher / Chen, Rong / Zeng, Kun / Guo, Jinkang / Qu, Yanyun / Li, Cuihua / Ahn, Namhyuk / Kang, Byungkon / Sohn, Kyung-Ah / Yuan, Yuan / Zhang, Jiawei / Pang, Jiahao / Xu, Xiangyu / Zhao, Yan / Deng, Wei / Ul Hussain, Sibt / Aadil, Muneeb / Rahim, Rafia / Cai, Xiaowang / Huang, Fang / Xu, Yueshu / Michelini, Pablo Navarrete / Zhu, Dan / Liu, Hanwen / Kim, Jun-Hyuk / Lee, Jong-Seok / Huang, Yiwen / Qiu, Ming / Jing, Liting / Zeng, Jiehang / Wang, Ying / Sharma, Manoj / Mukhopadhyay, Rudrabha / Upadhyay, Avinash / Koundinya, Sriharsha / Shukla, Ankit / Chaudhury, Santanu / Zhang, Zhe / Hu, Yu Hen / Fu, Lingzhi
This paper reviews the 2nd NTIRE challenge on single image super-resolution (restoration of rich details in a low resolution image) with focus on proposed solutions and results. The challenge had 4 tracks. Track 1 employed the standard bicubic downscaling setup, while Tracks 2, 3 and 4 had realistic unknown downgrading operators simulating camera image acquisition pipeline. The operators were learnable through provided pairs of low and high resolution train images. The tracks had 145, 114, 101, and 113 registered participants, resp., and 31 teams competed in the final testing phase. They gauge the state-of-the-art in single image super-resolution.
Publisher
IEEE
Issue Date
2018-06
Language
English
Citation

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.965 - 976

ISSN
2160-7508
DOI
10.1109/CVPRW.2018.00130
URI
http://hdl.handle.net/10203/274870
Appears in Collection
EE-Conference Papers(학술회의논문)
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