PointGT: A Method for Point-Cloud Classification and Segmentation Based on Local Geometric Transformation-Reference-Cited by-同舟云学术

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PointGT: A Method for Point-Cloud Classification and Segmentation Based on Local Geometric Transformation

Published:2024 Issue: Volume:26 Page:8052-8062
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Zhang Huang¹^ORCID,Wang Changshuo²^ORCID,Yu Long¹^ORCID,Tian Shengwei¹^ORCID,Ning Xin³^ORCID,Rodrigues Joel⁴^ORCID

Affiliation:

1. School of Software, Xinjiang University, Xinjiang, China

2. Cyber Security Research Centre, Nanyang Technological University, Singapore

3. Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China

4. Amazonas State University, Manaus, Brazil

Funder

Tianshan Yingcai Peiyang 2023

National Natural Science Foundation of China

Beijing Natural Science Foundation

Brazilian National Council for Scientific and Technological Development - CNPq

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6046/10384483/10462543.pdf?arnumber=10462543

Reference49 articles.

1. Real-time 3D Single Object Tracking with Transformer

2. Structure-Aware Graph Convolution Network for Point Cloud Parsing

3. Learning Discriminative Features by Covering Local Geometric Space for Point Cloud Analysis

4. Conditional random fields: Probabilistic models for segmenting and labeling sequence data;Lafferty,2001

5. Contextual classification with functional Max-Margin Markov Networks

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