DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Munchurl | ko |
dc.contributor.author | Sim, Hyeonjun | ko |
dc.date.accessioned | 2019-11-28T08:26:30Z | - |
dc.date.available | 2019-11-28T08:26:30Z | - |
dc.date.created | 2019-11-25 | - |
dc.date.created | 2019-11-25 | - |
dc.date.created | 2019-11-25 | - |
dc.date.issued | 2019-06-17 | - |
dc.identifier.citation | 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.1974 - 1984 | - |
dc.identifier.issn | 2160-7508 | - |
dc.identifier.uri | http://hdl.handle.net/10203/268692 | - |
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 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 deblurring problem. | - |
dc.language | English | - |
dc.publisher | Computer Vision Foundation | - |
dc.title | NTIRE 2019 Challenge on Video Deblurring: Methods and Results | - |
dc.type | Conference | - |
dc.identifier.wosid | 000569983600243 | - |
dc.identifier.scopusid | 2-s2.0-85083307173 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 1974 | - |
dc.citation.endingpage | 1984 | - |
dc.citation.publicationname | 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Long Beach, California | - |
dc.identifier.doi | 10.1109/CVPRW.2019.00249 | - |
dc.contributor.localauthor | Kim, Munchurl | - |
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