Name
Abstract | ||
|---|---|---|
We present a method for reconstructing triangle meshes from point clouds. Existing learning-based methods for mesh reconstruction mostly generate triangles individually, making it hard to create manifold meshes. We leverage the properties of 2D Delaunay triangulations to construct a mesh from manifold surface elements. Our method first estimates local geodesic neighborhoods around each point. We t... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/CVPR46437.2021.00009 | 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) |
Keywords | DocType | ISSN |
Manifolds,Learning systems,Surface reconstruction,Training data,Data models,Topology,Synchronization | Conference | 1063-6919 |
ISBN | Citations | PageRank |
978-1-6654-4509-2 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marie-Julie Rakotosaona | 1 | 5 | 1.53 |
| Paul Guerrero | 2 | 99 | 10.97 |
| Noam Aigerman | 3 | 215 | 12.60 |
| Niloy J. Mitra | 4 | 3813 | 176.15 |
| Maks Ovsjanikov | 5 | 2235 | 84.06 |