Learning on 3D Meshes With Laplacian Encoding and Pooling
3D models are commonly used in computer vision and graphics. With the wider availability of mesh data, an efficient and intrinsic deep learning approach to processing 3D meshes is in great need. Unlike images, 3D meshes have irregular connectivity, requiring careful design to capture relations in th...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 28(2022), 2 vom: 05. Feb., Seite 1317-1327
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| 1. Verfasser: |
Qiao, Yi-Ling
(VerfasserIn) |
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| Weitere Verfasser: |
Gao, Lin,
Yang, Jie,
Rosin, Paul L,
Lai, Yu-Kun,
Chen, Xilin |
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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 visualization and computer graphics
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| Schlagworte: | Journal Article |
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