Fine-Grained Human-Centric Tracklet Segmentation with Single Frame Supervision
In this paper, we target at the Fine-grAined human-Centric Tracklet Segmentation (FACTS) problem, where 12 human parts, e.g., face, pants, left-leg, are segmented. To reduce the heavy and tedious labeling efforts, FACTS requires only one labeled frame per video during training. The small size of hum...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 2 vom: 01. Feb., Seite 610-621
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| 1. Verfasser: |
Liu, Si
(VerfasserIn) |
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| Weitere Verfasser: |
Ren, Guanghui,
Sun, Yao,
Wang, Jinqiao,
Wang, Changhu,
Li, Bo,
Yan, Shuicheng |
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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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