Rotation-Invariant Point Cloud Representation for 3-D Model Recognition-Reference-Cited by-同舟云学术

Rotation-Invariant Point Cloud Representation for 3-D Model Recognition

Published:2022-10 Issue:10 Volume:52 Page:10948-10956
ISSN:2168-2267
Container-title:IEEE Transactions on Cybernetics
language:
Short-container-title:IEEE Trans. Cybern.

Author:

Wang Yan¹^ORCID,Zhao Yining¹^ORCID,Ying Shihui²^ORCID,Du Shaoyi³^ORCID,Gao Yue¹

Affiliation:

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

2. Department of Mathematics, School of Sciences, Shanghai University, Shanghai, China

3. Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Information Systems,Control and Systems Engineering,Software

Link

http://xplorestaging.ieee.org/ielx7/6221036/9895112/09739128.pdf?arnumber=9739128

Reference40 articles.

1. Multi-view Convolutional Neural Networks for 3D Shape Recognition

2. VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

3. Generalized Max Pooling

4. Adam: A method for stochastic optimization;kingma;arXiv 1412 6980,2017

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