NTIRE 2019 Challenge on Video Deblurring: Methods and Results
Seungjun Nah, Radu Timofte, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Kyoung Mu Lee, Xintao Wang, Kelvin C. K. Chan, Ke Yu, Chao Dong, Chen Change Loy, Yuchen Fan, Jiahui Yu, Ding Liu, Thomas S. Huang, Hyeonjun Sim, Munchurl Kim, Dongwon Park, Jisoo Kim · 2019
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.