3D-OAE: Occlusion Auto-Encoders for Self-Supervised Learning on Point Clouds-Reference-Cited by-同舟云学术

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3D-OAE: Occlusion Auto-Encoders for Self-Supervised Learning on Point Clouds

Published:2024-05-13 Issue: Volume:32 Page:15416-15423
ISSN:
Container-title:2024 IEEE International Conference on Robotics and Automation (ICRA)
language:
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Author:

Zhou Junsheng¹,Wen Xin²,Ma Baorui³,Liu Yu-Shen¹,Gao Yue¹,Fang Yi⁴,Han Zhizhong⁵

Affiliation:

1. School of Software, BNRist, Tsinghua University,Beijing,China

2. NVIDIA

3. School of Software, Tsinghua University and Beijing Academy of Artificial Intelligence,Beijing,China

4. New York University

5. Wayne State University,Department of Computer Science,USA

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609961/10609862/10610588.pdf?arnumber=10610588

Reference54 articles.

1. Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review

2. Towards subjective quality assessment of point cloud imaging in augmented reality

3. Uni3d: Exploring unified 3d representation at scale;Zhou

4. NeAF: Learning Neural Angle Fields for Point Normal Estimation

5. PCT: Point cloud transformer

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MuSic-UDF: Learning Multi-Scale dynamic grid representation for high-fidelity surface reconstruction from point clouds;Computers & Graphics;2024-09

2. 3D-OAE: Occlusion Auto-Encoders for Self-Supervised Learning on Point Clouds;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

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