NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

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dc.contributor.authorKim, Munchurlko
dc.contributor.authorChoi, Jae Seokko
dc.date.accessioned2017-12-05T02:32:40Z-
dc.date.available2017-12-05T02:32:40Z-
dc.date.created2017-11-30-
dc.date.created2017-11-30-
dc.date.issued2017-07-21-
dc.identifier.citation30th IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp.1110 - 1121-
dc.identifier.issn2160-7516-
dc.identifier.urihttp://hdl.handle.net/10203/227658-
dc.description.abstractThis paper reviews the first challenge on single image super-resolution (restoration of rich details in an low resolution image) with focus on proposed solutions and results. A new DIVerse 2K resolution image dataset (DIV2K) was employed. The challenge had 6 competitions divided into 2 tracks with 3 magnification factors each. Track 1 employed the standard bicubic downscaling setup, while Track 2 had unknown downscaling operators (blur kernel and decimation) but learnable through low and high res train images. Each competition had ~100 registered participants and 20 teams competed in the final testing phase. They gauge the state-of-the-art in single image super-resolution.-
dc.languageEnglish-
dc.publisherIEEE Computer Society and the Computer Vision Foundation (CVF)-
dc.titleNTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results-
dc.typeConference-
dc.identifier.wosid000426448300142-
dc.type.rimsCONF-
dc.citation.beginningpage1110-
dc.citation.endingpage1121-
dc.citation.publicationname30th IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationHonolulu, HI, USA-
dc.identifier.doi10.1109/CVPRW.2017.149-
dc.contributor.localauthorKim, Munchurl-
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EE-Conference Papers(학술회의논문)
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