Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering
We propose a deep autoencoder with graph topology inference and filtering to achieve compact representations of unorganized 3D point clouds in an unsupervised manner. Many previous works discretize 3D points to voxels and then use lattice-based methods to process and learn 3D spatial information; ho...
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Détails bibliographiques
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - (2019) vom: 11. Dez.
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| Auteur principal: |
Chen, Siheng
(Auteur) |
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| Autres auteurs: |
Duan, Chaojing,
Yang, Yaoqing,
Li, Duanshun,
Feng, Chen,
Tian, Dong |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2019
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Sujets: | Journal Article |
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