Learning Dense Correspondences for Non-Rigid Point Clouds With Two-Stage Regression
We propose a novel deep learning method to predict dense correspondences for partial point clouds of non-rigidly deformable targets. Dense correspondences are learned in the form of vertex displacements of a template mesh towards the point clouds. A two-stage regression framework is proposed to esti...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 30(2021) vom: 15., Seite 8468-8482 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2021
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
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