Few-Shot Point Cloud Semantic Segmentation via Contrastive Self-Supervision and Multi-Resolution Attention-Reference-Cited by-同舟云学术

Few-Shot Point Cloud Semantic Segmentation via Contrastive Self-Supervision and Multi-Resolution Attention

Published:2023-05-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Wang Jiahui¹,Zhu Haiyue²,Guo Haoren¹,Mamun Abdullah Al¹,Xiang Cheng¹,Lee Tong Heng¹

Affiliation:

1. National University of Singapore,College of Design and Engineering, Electrical and Computer Engineering,Singapore,117582

2. Singapore Institute of Manufacturing Technology (SIMTech),Agency for Science, Technology and Research (A*STAR),Singapore,Republic of Singapore,138634

Funder

National University of Singapore

A*STAR

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160429.pdf?arnumber=10160429

Reference31 articles.

1. Few-Shot Learning of Part-Specific Probability Space for 3D Shape Segmentation

2. Masked Self-Supervision for Remaining Useful Lifetime Prediction in Machine Tools

3. CAM/CAD Point Cloud Part Segmentation via Few-Shot Learning

4. Dataset and method for deep learning-based reconstruction of 3D CAD models containing machining features for mechanical parts

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