Deep Graph Matching Based Dense Correspondence Learning Between Non-Rigid Point Clouds-Reference-Cited by-同舟云学术

Deep Graph Matching Based Dense Correspondence Learning Between Non-Rigid Point Clouds

Published:2022-07 Issue:3 Volume:7 Page:5842-5849
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Luo Jiazheng¹^ORCID,Yuan Mingzhi¹^ORCID,Fu Kexue¹,Wang Manning¹^ORCID,Zhang Chenxi¹^ORCID

Affiliation:

1. Digital Medical Research Center, School of Basic Medical Science, Fudan University, Shanghai, China

Funder

Shanghai Science and Technology Innovation Action Plan

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/9750005/09737412.pdf?arnumber=9737412

Reference45 articles.

1. A method for registration of 3-D shapes

2. Optimal Step Nonrigid ICP Algorithms for Surface Registration

3. A Comprehensive Survey on Graph Neural Networks

4. Deep Closest Point: Learning Representations for Point Cloud Registration

5. Dynamic Graph CNN for Learning on Point Clouds

Cited by 5 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. Dense Correspondence Learning between Key Points in 3D C.elegans Based on Depth Map Matching;2024 3rd International Conference on Image Processing and Media Computing (ICIPMC);2024-05-17

2. Full-body pose reconstruction and correction in virtual reality for rehabilitation training;Frontiers in Neuroscience;2024-04-04

3. Decoupled deep hough voting for point cloud registration;Frontiers of Computer Science;2024-01-22

4. A dynamic graph aggregation framework for 3D point cloud registration;Engineering Applications of Artificial Intelligence;2023-04

5. Non-rigid point set registration: recent trends and challenges;Artificial Intelligence Review;2022-10-11