Hybrid Cross-Transformer-KPConv for Point Cloud Segmentation-Reference-Cited by-同舟云学术

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Hybrid Cross-Transformer-KPConv for Point Cloud Segmentation

Published:2024 Issue: Volume:31 Page:126-130
ISSN:1070-9908
Container-title:IEEE Signal Processing Letters
language:
Short-container-title:IEEE Signal Process. Lett.

Author:

Wen Shuhuan¹^ORCID,Li Pengjiang¹^ORCID,Zhang Hong²^ORCID

Affiliation:

1. Department of Key Lab of Industrial Computer Control Engineering of Hebei Province, Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Yanshan University, Qinhuangdao, China

2. Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China

Funder

National Natural Science Foundation of China

Royal Society of Britain

Hebei Innovation Capability Improvement Plan Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/97/10380231/10360248.pdf?arnumber=10360248

Reference35 articles.

1. Deep Learning for 3D Point Clouds: A Survey

2. Curvature-Variation-Inspired Sampling for Point Cloud Classification and Segmentation

3. PointNet: Deep learning on point sets for 3D classification and segmentation;Qi,2017

4. PointNet: Deep hierarchical feature learning on point sets in a metric space;Qi,2017

5. LatticeNet: fast spatio-temporal point cloud segmentation using permutohedral lattices

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