Neural Intrinsic Embedding for Non-Rigid Point Cloud Matching
Author:
Affiliation:
1. Tsinghua Shenzhen International Graduate School
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203556.pdf?arnumber=10203556
Reference56 articles.
1. NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go
2. Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence
3. CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds
4. The Perfect Match: 3D Point Cloud Matching With Smoothed Densities
5. Cyclic Functional Mapping: Self-supervised Correspondence Between Non-isometric Deformable Shapes
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1. Bijective upsampling and learned embedding for point clouds correspondences;Computers & Graphics;2024-08
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