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GeodesicEmbedding (GE): A High-Dimensional Embedding Approach for Fast
  Geodesic Distance Queries
v1v2 (latest)

GeodesicEmbedding (GE): A High-Dimensional Embedding Approach for Fast Geodesic Distance Queries

31 August 2021
Qianwei Xia
Juyong Zhang
Zheng Fang
Jin Li
Mingyue Zhang
Bailin Deng
Ying He
ArXiv (abs)PDFHTML

Papers citing "GeodesicEmbedding (GE): A High-Dimensional Embedding Approach for Fast Geodesic Distance Queries"

3 / 3 papers shown
Title
Surface-Aware Distilled 3D Semantic Features
Surface-Aware Distilled 3D Semantic Features
Lukas Uzolas
E. Eisemann
Petr Kellnhofer
3DPC3DH
119
0
0
24 Mar 2025
Learning the Geodesic Embedding with Graph Neural Networks
Learning the Geodesic Embedding with Graph Neural Networks
Bo Pang
Zhongtian Zheng
Guoping Wang
Peng-Shuai Wang
GNN
58
7
0
11 Sep 2023
Neural Intrinsic Embedding for Non-rigid Point Cloud Matching
Neural Intrinsic Embedding for Non-rigid Point Cloud Matching
Puhua Jiang
Min Sun
Ruqi Huang
3DPC
59
9
0
02 Mar 2023
1