EdgeNet: Deep metric learning for 3D shapes-Reference-Cited by-同舟云学术

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EdgeNet: Deep metric learning for 3D shapes

Published:2019-06 Issue: Volume:72 Page:19-33
ISSN:0167-8396
Container-title:Computer Aided Geometric Design
language:en
Short-container-title:Computer Aided Geometric Design

Author:

Chen Mingjia,Zou Qianfang,Wang Changbo,Liu Ligang

Funder

National Natural Science Foundation of China

Chinese Academy of Sciences

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Aerospace Engineering,Automotive Engineering,Modeling and Simulation

Reference62 articles.

1. Scape: shape completion and animation of people;Anguelov,2005

2. The wave kernel signature: a quantum mechanical approach to shape analysis;Aubry,2011

3. Shape context: a new descriptor for shape matching and object recognition;Belongie,2001

4. Characterizing shape using conformal factors;Ben-Chen,2008

5. Faust: dataset and evaluation for 3d mesh registration;Bogo,2014

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1. Unsupervised distribution-aware keypoints generation from 3D point clouds;Neural Networks;2024-05

2. Multi-scale and multi-level shape descriptor learning via a hybrid fusion network;Graphical Models;2022-01

3. 3D mesh segmentation via L0-constrained random walks;Multimedia Tools and Applications;2021-04-12

4. Object Synthesis by Learning Part Geometry with Surface and Volumetric Representations;Computer-Aided Design;2021-01

5. SAC-NMF-Driven Graphical Feature Analysis and Applications;Machine Learning and Knowledge Extraction;2020-12-08

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