NTIRE 2019 challenge on video deblurring: Methods and results

Seungjun Nah, ASRI
Radu Timofte, ETH Zürich
Sungyong Baik, ASRI
Seokil Hong, ASRI
Gyeongsik Moon, ASRI
Sanghyun Son, ASRI
Kyoung Mu Lee, ASRI
Xintao Wang, Chinese University of Hong Kong


This paper reviews the first NTIRE challenge on video deblurring (restoration of rich details and high frequency components from blurred video frames) with focus on the proposed solutions and results. A new REalistic and Diverse Scenes dataset (REDS) was employed. The challenge was divided into 2 tracks. Track 1 employed dynamic motion blurs while Track 2 had additional MPEG video compression artifacts. Each competition had 109 and 93 registered participants. Total 13 teams competed in the final testing phase. They gauge the state-of-the-art in video deblurring problem.