Generative Variational-Contrastive Learning for Self-Supervised Point Cloud Representation
Self-supervised representation learning for 3D point clouds has attracted increasing attention. However, existing methods in the field of 3D computer vision generally use fixed embeddings to represent the latent features, and impose hard constraints on the embeddings to make the latent feature value...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 9 vom: 19. Aug., Seite 6154-6166
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| 1. Verfasser: |
Wang, Bohua
(VerfasserIn) |
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| Weitere Verfasser: |
Tian, Zhiqiang,
Ye, Aixue,
Wen, Feng,
Du, Shaoyi,
Gao, Yue |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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