Understanding and Improving Features Learned in Deep Functional Maps

Author:

Attaiki Souhaib1,Ovsjanikov Maks1

Affiliation:

1. École Polytechnique, IP Paris,LIX

Publisher

IEEE

Reference81 articles.

1. PPFNet: Global Context Aware Local Features for Robust 3D Point Matching

2. Pointnet++: Deep hierarchical feature learning on point sets in a metric space;qi;Advances in neural information processing systems,2017

3. Shrec'16: Partial matching of deformable shapes;cosmo;Proc 3DOR,0

4. Pointnet: Deep learning on point sets for 3d classification and segmentation;qi;Proc Computer Vision and Pattern Recognition (CVPR),0

5. Deep orientation-aware functional maps: Tackling symmetry issues in Shape Matching

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Revisiting Map Relations for Unsupervised Non-Rigid Shape Matching;2024 International Conference on 3D Vision (3DV);2024-03-18

2. Unsupervised Representation Learning for Diverse Deformable Shape Collections;2024 International Conference on 3D Vision (3DV);2024-03-18

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