DC Field | Value | Language |
---|---|---|
dc.contributor.author | Oh, Tae-Hyun | ko |
dc.contributor.author | Joo, Kyungdon | ko |
dc.contributor.author | Joshi, Neel | ko |
dc.contributor.author | Wang, Baoyuan | ko |
dc.contributor.author | Kweon, In-So | ko |
dc.contributor.author | Kang, Sing Bing | ko |
dc.date.accessioned | 2017-12-05T02:20:30Z | - |
dc.date.available | 2017-12-05T02:20:30Z | - |
dc.date.created | 2017-11-29 | - |
dc.date.created | 2017-11-29 | - |
dc.date.created | 2017-11-29 | - |
dc.date.issued | 2017-10 | - |
dc.identifier.citation | 16th IEEE International Conference on Computer Vision (ICCV), pp.5170 - 5179 | - |
dc.identifier.issn | 1550-5499 | - |
dc.identifier.uri | http://hdl.handle.net/10203/227590 | - |
dc.description.abstract | Cinemagraphs are a compelling way to convey dynamic aspects of a scene. In these media, dynamic and still elements are juxtaposed to create an artistic and narrative experience. Creating a high-quality, aesthetically pleasing cinemagraph requires isolating objects in a semantically meaningful way and then selecting good start times and looping periods for those objects to minimize visual artifacts (such a tearing). To achieve this, we present a new technique that uses object recognition and semantic segmentation as part of an optimization method to automatically create cinemagraphs from videos that are both visually appealing and semantically meaningful. Given a scene with multiple objects, there are many cinemagraphs one could create. Our method evaluates these multiple candidates and presents the best one, as determined by a model trained to predict human preferences in a collaborative way. We demonstrate the effectiveness of our approach with multiple results and a user study. | - |
dc.language | English | - |
dc.publisher | IEEE Computer Society and the Computer Vision Foundation (CVF) | - |
dc.title | Personalized Cinemagraphs using Semantic Understanding and Collaborative Learning | - |
dc.type | Conference | - |
dc.identifier.wosid | 000425498405027 | - |
dc.identifier.scopusid | 2-s2.0-85041922865 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 5170 | - |
dc.citation.endingpage | 5179 | - |
dc.citation.publicationname | 16th IEEE International Conference on Computer Vision (ICCV) | - |
dc.identifier.conferencecountry | IT | - |
dc.identifier.conferencelocation | Venice Convention Center, Venice | - |
dc.identifier.doi | 10.1109/ICCV.2017.552 | - |
dc.contributor.localauthor | Kweon, In-So | - |
dc.contributor.nonIdAuthor | Oh, Tae-Hyun | - |
dc.contributor.nonIdAuthor | Joo, Kyungdon | - |
dc.contributor.nonIdAuthor | Joshi, Neel | - |
dc.contributor.nonIdAuthor | Wang, Baoyuan | - |
dc.contributor.nonIdAuthor | Kang, Sing Bing | - |
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