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NTIRE 2018 Challenge on Single Image Super-Resolution: Methods and Results
- Author(s)
- Timofte, Radu, Gu, Shuhang, Wu, Jiqing, Gool, Luc Van, Zhang, Lei, Yang, Ming-Hsuan, Haris, Muhammad, Shakhnarovich, Greg, Ukita, Norimichi, Hu, Shijia, Yijie, Webster Bei, Hui, Zheng, Jiang, Xiao, Gu, Yanan, Liu, Jie, Wang, Yifan, Perazzi, Federico, McWilliams, Brian, Sorkine-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, Seo, Junghoon, Jeon, Taegyun, Koo, Jamyoung, Jeon, Seunghyun, Kim, Soo Ye, Choi, Jae-Seok, Ki, Sehwan, Seo, Soomin, Sim, Hyeonjun, Kim, Saehun, Kim, Munchurl, Chen, Rong, Zeng, Kun, Guo, Jinkang, Qu, Yanyun, Li, Cuihua, Ah, Namhyuk, Kang, Byungkon, Sohn. Kyung-Ah, Yuan, Yuan, Zhang, Jiawei, Pang, Jiahao, Xu, Xiangyu, Zhao, Yan, Deng, Wei, Hussain, Sibt Ul, 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
- Issued Date
- 2018-06-18
- Citation
- CVPR 2018: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pp.852 - 863
- Abstract
- 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 Computer Society
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