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

Seungjun Nah, Radu Timofte, Shuhang Gu, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Kyoung Mu Lee; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019, pp. 0-0

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.

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[bibtex]
@InProceedings{Nah_2019_CVPR_Workshops,
author = {Nah, Seungjun and Timofte, Radu and Gu, Shuhang and Baik, Sungyong and Hong, Seokil and Moon, Gyeongsik and Son, Sanghyun and Mu Lee, Kyoung},
title = {NTIRE 2019 Challenge on Video Super-Resolution: Methods and Results},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}