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NTIRE 2019 Challenge on Video Deblurring: Methods and Results

DC Field Value Language
dc.contributor.authorNah, Seungjun-
dc.contributor.authorTimofte, Radu-
dc.contributor.authorBaik, Sungyong-
dc.contributor.authorHong, Seokil-
dc.contributor.authorMoon, Gyeongsik-
dc.contributor.authorSon, Sanghyun-
dc.contributor.authorLee, Kyoung Mu-
dc.contributor.authorWang, Xintao-
dc.contributor.authorChan, Kelvin C. K.-
dc.contributor.authorYu, Ke-
dc.contributor.authorDong, Chao-
dc.contributor.authorLoy, Chen Change-
dc.contributor.authorFan, Yuchen-
dc.contributor.authorYu, Jiahui-
dc.contributor.authorLiu, Ding-
dc.contributor.authorHuang, Thomas S.-
dc.contributor.authorSim, Hyeonjun-
dc.contributor.authorKim, Munchurl-
dc.contributor.authorPark, Dongwon-
dc.contributor.authorKim, Jisoo-
dc.contributor.authorChun, Se Young-
dc.contributor.authorHaris, Muhammad-
dc.contributor.authorShakhnarovich, Greg-
dc.contributor.authorUkita, Norimichi-
dc.contributor.authorZamir, Syed Waqas-
dc.contributor.authorArora, Aditya-
dc.contributor.authorKhan, Salman-
dc.contributor.authorKhan, Fahad Shahbaz-
dc.contributor.authorShao, Ling-
dc.contributor.authorGupta, Rahul Kumar-
dc.contributor.authorChudasama, Vishal-
dc.contributor.authorPatel, Heena-
dc.contributor.authorUpla, Kishor-
dc.contributor.authorFan, Hongfei-
dc.contributor.authorLi, Guo-
dc.contributor.authorZhang, Yumei-
dc.contributor.authorLi, Xiang-
dc.contributor.authorZhang, Wenjie-
dc.contributor.authorHe, Qingwen-
dc.contributor.authorPurohit, Kuldeep-
dc.contributor.authorRajagopalan, A. N.-
dc.contributor.authorKim, Jeonghun-
dc.contributor.authorTofighi, Mohammad-
dc.contributor.authorGuo, Tiantong-
dc.contributor.authorMonga, Vishal-
dc.date.accessioned2022-10-19T00:30:41Z-
dc.date.available2022-10-19T00:30:41Z-
dc.date.created2022-10-17-
dc.date.issued2019-06-
dc.identifier.citation2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2019), pp.1974-1984-
dc.identifier.issn2160-7508-
dc.identifier.urihttps://hdl.handle.net/10371/186439-
dc.description.abstractThis 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 de blurring problem.-
dc.language영어-
dc.publisherIEEE-
dc.titleNTIRE 2019 Challenge on Video Deblurring: Methods and Results-
dc.typeArticle-
dc.identifier.doi10.1109/CVPRW.2019.00249-
dc.citation.journaltitle2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2019)-
dc.identifier.wosid000569983600243-
dc.identifier.scopusid2-s2.0-85083307173-
dc.citation.endpage1984-
dc.citation.startpage1974-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorLee, Kyoung Mu-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
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