DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ju, Minjeong | ko |
dc.contributor.author | Ryu, Hobin | ko |
dc.contributor.author | Moon, Sangkeun | ko |
dc.contributor.author | Yoo, Chang-Dong | ko |
dc.date.accessioned | 2021-10-27T08:30:23Z | - |
dc.date.available | 2021-10-27T08:30:23Z | - |
dc.date.created | 2021-10-19 | - |
dc.date.created | 2021-10-19 | - |
dc.date.issued | 2020-09 | - |
dc.identifier.citation | IEEE International Conference on Image Processing, ICIP 2020, pp.703 - 707 | - |
dc.identifier.issn | 1522-4880 | - |
dc.identifier.uri | http://hdl.handle.net/10203/288360 | - |
dc.description.abstract | This paper proposes a multi-task learning framework for fine-grained visual categorization (FGVC) referred to as Generic-Attribute-Pose Network (GAPNet) that is capable of attending discriminating parts depending on the pose and part-attribute of an object using multi-attribute attention. FGVC is a challenging task that involves categorical data with small inter-class variation and large intra-class variation. Multi-Attribute Attention Module (MAAM) guides the GAPNet to focus on multiple parts of the image feature by emphasizing appropriate feature channels given both pose and part-attribute features. Experiments on Caltech-UCSD Birds and NABirds datasets demonstrate that GAPNet is competitive with other state-of-the-art methods, and ablation study on GAPNet conditioned on pose and part-attribute feature shows that GAPNet performs best when conditioned on both pose and part-attribute features. | - |
dc.language | English | - |
dc.publisher | IEEE | - |
dc.title | GAPNET: GENERIC-ATTRIBUTE-POSE NETWORK FOR FINE-GRAINED VISUAL CATEGORIZATION USING MULTI-ATTRIBUTE ATTENTION MODULE | - |
dc.type | Conference | - |
dc.identifier.wosid | 000646178500140 | - |
dc.identifier.scopusid | 2-s2.0-85098625582 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 703 | - |
dc.citation.endingpage | 707 | - |
dc.citation.publicationname | IEEE International Conference on Image Processing, ICIP 2020 | - |
dc.identifier.conferencecountry | AR | - |
dc.identifier.conferencelocation | Virtual | - |
dc.identifier.doi | 10.1109/ICIP40778.2020.9190875 | - |
dc.contributor.localauthor | Yoo, Chang-Dong | - |
dc.contributor.nonIdAuthor | Ju, Minjeong | - |
dc.contributor.nonIdAuthor | Ryu, Hobin | - |
dc.contributor.nonIdAuthor | Moon, Sangkeun | - |
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