PCL: Point Contrast and Labeling for Weakly Supervised Point Cloud Semantic Segmentation-Reference-Cited by-同舟云学术

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PCL: Point Contrast and Labeling for Weakly Supervised Point Cloud Semantic Segmentation

Published:2024 Issue: Volume:26 Page:8902-8914
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Du Anan¹^ORCID,Zhou Tianfei²^ORCID,Pang Shuchao³^ORCID,Wu Qiang⁴^ORCID,Zhang Jian⁴^ORCID

Affiliation:

1. Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, Sydney, NSW, Australia

2. Computer Vision Lab, ETH Zurich, Zurich, Switzerland

3. School of Cyber Science and Engineering, Nanjing University of Science and Technology, Nanjing, China

4. Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, NSW, Australia

Funder

Jiangsu Autonomous Driving Technology Engineering Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6046/10384483/10487013.pdf?arnumber=10487013

Reference53 articles.

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

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

3. PointCNN: Convolution on x-transformed points;Li,2018

4. Tangent Convolutions for Dense Prediction in 3D

5. PointConv: Deep Convolutional Networks on 3D Point Clouds

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