Progressive Learning of Category-Consistent Multi-Granularity Features for Fine-Grained Visual Classification
Fine-grained visual classification (FGVC) is much more challenging than traditional classification tasks due to the inherently subtle intra-class object variations. Recent works are mainly part-driven (either explicitly or implicitly), with the assumption that fine-grained information naturally rests...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 12 vom: 09. Dez., Seite 9521-9535
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| 1. Verfasser: |
Du, Ruoyi
(VerfasserIn) |
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| Weitere Verfasser: |
Xie, Jiyang,
Ma, Zhanyu,
Chang, Dongliang,
Song, Yi-Zhe,
Guo, Jun |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2022
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't |
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