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Chun, Se Young
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dc.citation.conferencePlace US -
dc.citation.title IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) -
dc.contributor.author Nah, Seungjun -
dc.contributor.author Timofte, Radu -
dc.contributor.author Baik, Sungyong -
dc.contributor.author Hong, Seokil -
dc.contributor.author Moon, Gyeongsik -
dc.contributor.author Son, Sanghyun -
dc.contributor.author Lee, Kyoung Mu -
dc.contributor.author Wang, Xintao -
dc.contributor.author Chan, Kelvin C.K. -
dc.contributor.author Yu, Ke -
dc.contributor.author Dong, Chao -
dc.contributor.author Loy, Chen Change -
dc.contributor.author Fan, Yuchen -
dc.contributor.author Yu, Jiahui -
dc.contributor.author Liu, Ding -
dc.contributor.author Huang, Thomas S. -
dc.contributor.author Sim, Hyeonjun -
dc.contributor.author Kim, Munchurl -
dc.contributor.author Park, Dongwon -
dc.contributor.author Kim, Jisoo -
dc.contributor.author Chun, Se Young -
dc.contributor.author Haris, Muhammad -
dc.contributor.author Shakhnarovich, Greg -
dc.contributor.author Ukita, Norimichi -
dc.contributor.author Zamir, Syed Waqas -
dc.contributor.author Arora, Aditya -
dc.contributor.author Khan, Salman -
dc.contributor.author Khan, Fahad Shahbaz -
dc.contributor.author Shao, Ling -
dc.contributor.author Gupta, Rahul Kumar -
dc.contributor.author Chudasama, Vishal -
dc.contributor.author Patel, Heena -
dc.contributor.author Upla, Kishor -
dc.contributor.author Fan, Hongfei -
dc.contributor.author Li, Guo -
dc.contributor.author Zhang, Yumei -
dc.contributor.author Li, Xiang -
dc.contributor.author Zhang, Wenjie -
dc.contributor.author He, Qingwen -
dc.contributor.author Purohit, Kuldeep -
dc.contributor.author Rajagopalan, A. N. -
dc.contributor.author Kim, Jeonghun -
dc.contributor.author Tofighi, Mohammad -
dc.contributor.author Guo, Tiantong -
dc.contributor.author Monga, Vishal -
dc.date.accessioned 2024-02-01T00:08:41Z -
dc.date.available 2024-02-01T00:08:41Z -
dc.date.created 2020-01-08 -
dc.date.issued 2019-06-17 -
dc.description.abstract 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 Di- verse Scenes dataset (REDS) was employed. The challenge was divided into 2 tracks. Track 1 employed dynamic mo- tion blurs while Track 2 had additional MPEG video com- pression artifacts. Each competition had 109 and 93 reg- istered participants. Total 13 teams competed in the final
testing phase. They gauge the state-of-the-art in video de- blurring problem.
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dc.identifier.bibliographicCitation IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/79659 -
dc.publisher IEEE/CVF -
dc.title NTIRE 2019 Challenge on Video Deblurring: Methods and Results -
dc.type Conference Paper -
dc.date.conferenceDate 2019-06-16 -

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