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NTIRE 2019 Challenge on Video Super-Resolution: Methods and Results

Cited 17 time in Web of Science Cited 32 time in Scopus
Authors

Nah, Seungjun; Timofte, Radu; Gu, Shuhang; Baik, Sungyong; Hong, Seokil; Moon, Gyeongsik; Son, Sanghyun; Lee, Kyoung Mu; Wang, Xintao; Chan, Kelvin C. K.; Yu, Ke; Dong, Chao; Loy, Chen Change; Fan, Yuchen; Yu, Jiahui; Liu, Ding; Huang, Thomas S.; Liu, Xiao; Li, Chao; He, Dongliang; Ding, Yukang; Wen, Shilei; Porikli, Fatih; Kalarot, Ratheesh; Haris, Muhammad; Shakhnarovich, Greg; Ukita, Norimichi; Yi, Peng; Wang, Zhongyuan; Jiang, Kui; Jiang, Junjun; Ma, Jiayi; Dong, Hang; Zhang, Xinyi; Hu, Zhe; Kim, Kwanyoung; Kang, Dong Un; Chun, Se Young; Purohit, Kuldeep; Rajagopalan, A. N.; Tian, Yapeng; Zhang, Yulun; Fu, Yun; Xu, Chenliang; Tekalp, A. Murat; Yilmaz, M. Akin; Korkmaz, Cansu; Sharma, Manoj; Makwana, Megh; Badhwar, Anuj; Singh, Ajay Pratap; Upadhyay, Avinash; Mukhopadhyay, Rudrabha; Shukla, Ankit; Khanna, Dheeraj; Mandal, A. S.; Chaudhury, Santanu; Miao, Si; Zhu, Yongxin; Huo, Xiao

Issue Date
2019-06
Publisher
IEEE
Citation
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2019), pp.1985-1995
Abstract
This paper reviews the first NTIRE challenge on video super-resolution (restoration of rich details in low resolution video frames) with focus on proposed solutions and results. A new REalistic and Diverse Scenes dataset (REDS) was employed. The challenge was divided into 2 tracks. Track 1 employed standard bicubic downscaling setup while Track 2 had realistic dynamic motion blurs. Each competition had 124 and 104 registered participants. There were total 14 teams in the final testing phase. They gauge the state-of-the-art in video super-resolution.
ISSN
2160-7508
URI
https://hdl.handle.net/10371/186440
DOI
https://doi.org/10.1109/CVPRW.2019.00250
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