NTIRE 2020 challenge on image and video deblurring

Nah，Seungjun1; Son，Sanghyun1; Timofte，Radu2; Lee，Kyoung Mu1; Tseng，Yu1; Xu，Yu Syuan1; Chiang，Cheng Ming3; Tsai，Yi Min3; Brehm，Stephan4; Scherer，Sebastian4; Xu，Dejia5; Chu，Yihao6; Sun，Qingyan7; Jiang，Jiaqin8; Duan，Lunhao8; Yao，Jian8; Purpohit，Kuldeep9; Suin，Maitreya9; Rajagopalan，A. N.9; Ito，Yuichi10; Hrishikesh，H. P.S.10; Puthussery，Densen10; Akhil，A. K.10; Jiji，V. C.10; Kim，Guisik11; Deepa，P. L.12; Xiong，Zhiwei13; Huang，Jie13; Liu，Dong13; Kim，Sangmin14; Nam，Hyungjoon14; Kim，Jisu14; Jeong，Jechang14; Huang，Shihua15; Fan，Yuchen16; Yu，Jiahui16; Yu，Haichao16; Huang，Thomas S.16; Zhou，Ya17; Li，Xin18; Liu，Sen19; Chen，Zhibo19; Dutta，Saikat20; Das，Sourya Dipta21; Garg，Shivam22; Sprague，Daniel23; Patel，Bhrij23; Huck，Thomas23

10.1109/CVPRW50498.2020.00216

2020-06-01

2160-7508

2160-7516

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

2020-June

1662-1675

Motion blur is one of the most common degradation artifacts in dynamic scene photography. This paper reviews the NTIRE 2020 Challenge on Image and Video Deblurring. In this challenge, we present the evaluation results from 3 competition tracks as well as the proposed solutions. Track 1 aims to develop single-image deblurring methods focusing on restoration quality. On Track 2, the image deblurring methods are executed on a mobile platform to find the balance of the running speed and the restoration accuracy. Track 3 targets developing video deblurring methods that exploit the temporal relation between input frames. In each competition, there were 163, 135, and 102 registered participants and in the final testing phase, 9, 4, and 7 teams competed. The winning methods demonstrate the state-of-the-art performance on image and video deblurring tasks.

其他

英语

EI

20203609136958

Computer vision ; Image enhancement

Computer Applications:723.5 ; Vision:741.2

2-s2.0-85090113691

Scopus

1.Seoul National University,South Korea
2.Department of ECE,ASRI,SNU,South Korea
3.Computer Vision Lab,ETH Zurich,Switzerland
4.MediaTek Inc.,Taiwan
5.University of Augsburg,Multimedia Computing and Computer Vision Lab,Germany
6.Peking University,China
7.Beijing University of Posts and Telecommunications,China
8.Beijing Jiaotong University,China
9.Wuhan University,China
10.Indian Institute of Technology Madras,India
11.Vermilion,United States
12.College of Engineering Trivandrum,India
13.CVML,Chung-Ang University,South Korea
14.APJ Abdul Kalam Technological University,India
15.University of Science and Technology of China,China
16.Image Communication Signal Processing Laboratory,Hanyang University,South Korea
17.Southern University of Science and Technology,China
18.University of Illinois at Urbana-Champaign,United States
19.CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System,University of Science and Technology of China,China
20.IIT Madra,India
21.Jadavpur University,India
22.University of Texas at Austin,USA,United States
23.Duke University Computer Science Department,United States

Nah，Seungjun,Son，Sanghyun,Timofte，Radu,et al. NTIRE 2020 challenge on image and video deblurring[C],2020:1662-1675.