Generative Variational-Contrastive Learning for Self-Supervised Point Cloud Representation-Reference-Cited by-同舟云学术

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Generative Variational-Contrastive Learning for Self-Supervised Point Cloud Representation

Published:2024-09 Issue:9 Volume:46 Page:6154-6166
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Wang Bohua¹^ORCID,Tian Zhiqiang¹^ORCID,Ye Aixue²^ORCID,Wen Feng²^ORCID,Du Shaoyi³^ORCID,Gao Yue⁴^ORCID

Affiliation:

1. School of Software Engineering, Xi’an Jiaotong University, Xi’an, China

2. Huawei Noah's Ark Lab, Huawei Technologies Company Ltd., Beijing, China

3. National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, National Engineering Research Center for Visual Information and Applications, and Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China

4. BNRist, KLISS, School of Software, BLBCI, THUIBCS, Tsinghua University, Beijing, China

Funder

National Science and Technology Major Project of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/34/10627928/10475594.pdf?arnumber=10475594

Reference55 articles.

1. PointNet: Deep learning on point sets for 3D classification and segmentation;Qi

2. PointNet : Deep hierarchical feature learning on point sets in a metric space;Qi

3. Dynamic Graph CNN for Learning on Point Clouds

4. Learning of 3D Graph Convolution Networks for Point Cloud Analysis

5. Rethinking network design and local geometry in point cloud: A simple residual MLP framework;Ma

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