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NTIRE 2021 Challenge on Image Deblurring

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dc.contributor.authorNah, Seungjun-
dc.contributor.authorSon, Sanghyun-
dc.contributor.authorLee, Suyoung-
dc.contributor.authorTimofte, Radu-
dc.contributor.authorLee, Kyoung Mu-
dc.contributor.authorChen, Liangyu-
dc.contributor.authorZhang, Jie-
dc.contributor.authorLu, Xin-
dc.contributor.authorChu, Xiaojie-
dc.contributor.authorChen, Chengpeng-
dc.contributor.authorXiong, Zhiwei-
dc.contributor.authorXu, Ruikang-
dc.contributor.authorXiao, Zeyu-
dc.contributor.authorHuang, Jie-
dc.contributor.authorZhang, Yueyi-
dc.contributor.authorXi, Si-
dc.contributor.authorWei, Jia-
dc.contributor.authorBai, Haoran-
dc.contributor.authorCheng, Songsheng-
dc.contributor.authorWei, Hao-
dc.contributor.authorSun, Long-
dc.contributor.authorTang, Jinhui-
dc.contributor.authorPan, Jinshan-
dc.contributor.authorLee, Donghyeon-
dc.contributor.authorLee, Chulhee-
dc.contributor.authorKim, Taesung-
dc.contributor.authorWang, Xiaobing-
dc.contributor.authorZhang, Dafeng-
dc.contributor.authorPan, Zhihong-
dc.contributor.authorLin, Tianwei-
dc.contributor.authorWu, Wenhao-
dc.contributor.authorHe, Dongliang-
dc.contributor.authorLi, Baopu-
dc.contributor.authorLi, Boyun-
dc.contributor.authorXi, Teng-
dc.contributor.authorZhang, Gang-
dc.contributor.authorLiu, Jingtuo-
dc.contributor.authorHan, Junyu-
dc.contributor.authorDing, Errui-
dc.contributor.authorTao, Guangpin-
dc.contributor.authorChu, Wenqing-
dc.contributor.authorCao, Yun-
dc.contributor.authorLuo, Donghao-
dc.contributor.authorTai, Ying-
dc.contributor.authorLu, Tong-
dc.contributor.authorWang, Chengjie-
dc.contributor.authorLi, Jilin-
dc.contributor.authorHuang, Feiyue-
dc.contributor.authorChen, Hanting-
dc.contributor.authorChen, Shuaijun-
dc.contributor.authorGuo, Tianyu-
dc.contributor.authorWang, Yunhe-
dc.contributor.authorZamir, Syed Waqas-
dc.contributor.authorArora, Aditya-
dc.contributor.authorKhan, Salman-
dc.contributor.authorHayat, Munawar-
dc.contributor.authorKhan, Fahad Shahbaz-
dc.contributor.authorShao, Ling-
dc.contributor.authorZuo, Yushen-
dc.contributor.authorOu, Yimin-
dc.contributor.authorChai, Yuanjun-
dc.contributor.authorShi, Lei-
dc.contributor.authorLiu, Shuai-
dc.contributor.authorLei, Lei-
dc.contributor.authorFeng, Chaoyu-
dc.contributor.authorZeng, Kai-
dc.contributor.authorYao, Yuying-
dc.contributor.authorLiu, Xinran-
dc.contributor.authorZhang, Zhizhou-
dc.contributor.authorHuang, Huacheng-
dc.contributor.authorZhang, Yunchen-
dc.contributor.authorJiang, Mingchao-
dc.contributor.authorZou, Wenbin-
dc.contributor.authorMiao, Si-
dc.contributor.authorKim, Yangwoo-
dc.contributor.authorSun, Yuejin-
dc.contributor.authorDeng, Senyou-
dc.contributor.authorRen, Wenqi-
dc.contributor.authorCao, Xiaochun-
dc.contributor.authorWang, Tao-
dc.contributor.authorSuin, Maitreya-
dc.contributor.authorRajagopalan, A. N.-
dc.contributor.authorVinh Van Duong-
dc.contributor.authorThuc Huu Nguyen-
dc.contributor.authorYim, Jonghoon-
dc.contributor.authorJeon, Byeungwoo-
dc.contributor.authorLi, Ru-
dc.contributor.authorXie, Junwei-
dc.contributor.authorHan, Jong-Wook-
dc.contributor.authorChoi, Jun-Ho-
dc.contributor.authorKim, Jun-Hyuk-
dc.contributor.authorLee, Jong-Seok-
dc.contributor.authorZhang, Jiaxin-
dc.contributor.authorPeng, Fan-
dc.contributor.authorSvitov, David-
dc.contributor.authorPakulich, Dmitry-
dc.contributor.authorKim, Jaeyeob-
dc.contributor.authorJeong, Jechang-
dc.date.accessioned2023-05-03T14:24:55Z-
dc.date.available2023-05-03T14:24:55Z-
dc.date.created2022-01-05-
dc.date.issued2021-06-
dc.identifier.issn2160-7508-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/185430-
dc.description.abstractMotion blur is a common photography artifact in dynamic environments that typically comes jointly with the other types of degradation. This paper reviews the NTIRE 2021 Challenge on Image Deblurring. In this challenge report, we describe the challenge specifics and the evaluation results from the 2 competition tracks with the proposed solutions. While both the tracks aim to recover a high-quality clean image from a blurry image, different artifacts are jointly involved. In track 1, the blurry images are in a low resolution while track 2 images are compressed in JPEG format. In each competition, there were 338 and 238 registered participants and in the final testing phase, 18 and 17 teams competed. The winning methods demonstrate the state-of-the-art performance on the image deblurring task with the jointly combined artifacts.-
dc.language영어-
dc.language.isoen-
dc.publisherIEEE COMPUTER SOC-
dc.titleNTIRE 2021 Challenge on Image Deblurring-
dc.typeArticle-
dc.contributor.affiliatedAuthorJeong, Jechang-
dc.identifier.doi10.1109/CVPRW53098.2021.00025-
dc.identifier.scopusid2-s2.0-85116001680-
dc.identifier.wosid000705890200017-
dc.identifier.bibliographicCitation2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGITION WORKSHOPS (CVPRW 2021), pp.149 - 165-
dc.relation.isPartOf2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGITION WORKSHOPS (CVPRW 2021)-
dc.citation.title2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGITION WORKSHOPS (CVPRW 2021)-
dc.citation.startPage149-
dc.citation.endPage165-
dc.type.rimsART-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordPlusARTIFACTS-
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