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전세영

Chun, Se Young
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dc.citation.conferencePlace US -
dc.citation.conferencePlace Seattle, WA, USA -
dc.citation.endPage 2076 -
dc.citation.startPage 2058 -
dc.citation.title IEEE Conference on Computer Vision and Pattern Recognition -
dc.contributor.author Lugmayr, A. -
dc.contributor.author Danelljan, M. -
dc.contributor.author Timofte, R. -
dc.contributor.author Ahn, N. -
dc.contributor.author Bai, D. -
dc.contributor.author Cai, J. -
dc.contributor.author Cao, Y. -
dc.contributor.author Chen, J. -
dc.contributor.author Cheng, K. -
dc.contributor.author Chun, Se Young -
dc.contributor.author Deng, W. -
dc.contributor.author El-Khamy, M. -
dc.contributor.author Ho, C.M. -
dc.contributor.author Ji, X. -
dc.contributor.author Kheradmand, A. -
dc.contributor.author Kim, G. -
dc.contributor.author Ko, H. -
dc.contributor.author Lee, K. -
dc.contributor.author Lee, J. -
dc.contributor.author Li, H. -
dc.contributor.author Liu, Z. -
dc.contributor.author Liu, Z.-S. -
dc.contributor.author Liu, S. -
dc.contributor.author Lu, Y. -
dc.contributor.author Meng, Z. -
dc.contributor.author Michelini, P.N. -
dc.contributor.author Micheloni, C. -
dc.contributor.author Prajapati, K. -
dc.contributor.author Ren, H. -
dc.contributor.author Seo, Y.H. -
dc.contributor.author Siu, W.-C. -
dc.contributor.author Sohn, K.-A. -
dc.contributor.author Tai, Y. -
dc.contributor.author Umer, R.M. -
dc.contributor.author Wang, S. -
dc.contributor.author Wang, H. -
dc.contributor.author Wu, T.H. -
dc.contributor.author Wu, H. -
dc.contributor.author Yang, B. -
dc.contributor.author Yang, F. -
dc.contributor.author Yoo, Jaejun -
dc.contributor.author Zhao, T. -
dc.contributor.author Zhou, Y. -
dc.contributor.author Zhuo, H. -
dc.contributor.author Zong, Z. -
dc.contributor.author Zou, X. -
dc.date.accessioned 2024-01-31T23:06:53Z -
dc.date.available 2024-01-31T23:06:53Z -
dc.date.created 2021-08-19 -
dc.date.issued 2020-06 -
dc.description.abstract This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resolution images are unavailable. For training, only one set of source input images is therefore provided along with a set of unpaired high-quality target images. In Track 1: Image Processing artifacts, the aim is to super-resolve images with synthetically generated image processing artifacts. This allows for quantitative benchmarking of the approaches w.r.t. a ground-truth image. In Track 2: Smartphone Images, real low-quality smart phone images have to be super-resolved. In both tracks, the ultimate goal is to achieve the best perceptual quality, evaluated using a human study. This is the second challenge on the subject, following AIM 2019, targeting to advance the state-of-the-art in super-resolution. To measure the performance we use the benchmark protocol from AIM 2019. In total 22 teams competed in the final testing phase, demonstrating new and innovative solutions to the problem. © 2020 IEEE. -
dc.identifier.bibliographicCitation IEEE Conference on Computer Vision and Pattern Recognition, pp.2058 - 2076 -
dc.identifier.doi 10.1109/CVPRW50498.2020.00255 -
dc.identifier.issn 2160-7508 -
dc.identifier.scopusid 2-s2.0-85090110747 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/78510 -
dc.language 영어 -
dc.publisher IEEE Computer Society -
dc.title NTIRE 2020 challenge on real-world image super-resolution: Methods and results -
dc.type Conference Paper -
dc.date.conferenceDate 2020-06-14 -

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