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  Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding

Shi, X., Xu, X., Zhang, W., Zhu, X., Foo, C. S., & Jia, K. (2022). Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding. In 26th International Conference on Pattern Recognition / 8th International Workshop on Image Mining - Theory and Applications (pp. 5045-5051). Piscataway, NJ: IEEE. doi:10.1109/ICPR56361.2022.9956506.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000C-9BC0-C Version Permalink: https://hdl.handle.net/21.11116/0000-000C-B949-2
Genre: Conference Paper

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 Creators:
Shi, Xian1, Author
Xu, Xun1, Author
Zhang, Wanyue2, Author           
Zhu, Xiatian1, Author
Foo, Chuan Sheng1, Author
Jia, Kui1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Visual Computing and Artificial Intelligence, MPI for Informatics, Max Planck Society, ou_3311330              

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Language(s): eng - English
 Dates: 2022
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Shi_ICPR22
DOI: 10.1109/ICPR56361.2022.9956506
 Degree: -

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Title: 26th International Conference on Pattern Recognition / 8th International Workshop on Image Mining - Theory and Applications
Place of Event: Montreal, Canada
Start-/End Date: 2022-08-21 - 2022-08-25

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Title: 26th International Conference on Pattern Recognition / 8th International Workshop on Image Mining - Theory and Applications
  Abbreviation : ICPR 2022 / IMTA 2022
  Other : IMTA 2022
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 5045 - 5051 Identifier: ISBN: 978-1-6654-9062-7