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Improving Semantic Analysis on Point Clouds via Auxiliary Supervision of Local Geometric Priors
Tang, Lulu1; Chen, Ke2,3; Wu, Chaozheng2; Hong, Yu4; Jia, Kui3,5; Yang, Zhi Xin1
2022-06-01
Source PublicationIEEE Transactions on Cybernetics
ABS Journal Level3
ISSN2168-2267
Volume52Issue:6Pages:4949-4959
Abstract

Existing deep learning algorithms for point cloud analysis mainly concern discovering semantic patterns from the global configuration of local geometries in a supervised learning manner. However, very few explore geometric properties revealing local surface manifolds embedded in 3-D Euclidean space to discriminate semantic classes or object parts as additional supervision signals. This article is the first attempt to propose a unique multitask geometric learning network to improve semantic analysis by auxiliary geometric learning with local shape properties, which can be either generated via physical computation from point clouds themselves as self-supervision signals or provided as privileged information. Owing to explicitly encoding local shape manifolds in favor of semantic analysis, the proposed geometric self-supervised and privileged learning algorithms can achieve superior performance to their backbone baselines and other state-of-the-art methods, which are verified in the experiments on the popular benchmarks.

KeywordGeometric Properties Point Clouds Privileged Learning Self-supervised Learning Semantic Analysis
DOI10.1109/TCYB.2020.3025798
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000819019200083
Scopus ID2-s2.0-85132454336
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Citation statistics
Document TypeJournal article
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Faculty of Science and Technology
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Corresponding AuthorJia, Kui; Yang, Zhi Xin
Affiliation1.University Of Macau, State Key Laboratory Of Internet Of Things For Smart City, Department Of Electromechanical Engineering, Macao
2.South China University Of Technology, School Of Electronic And Information Engineering, Guangzhou, 510641, China
3.Peng Cheng Laboratory, Shenzhen, 518005, China
4.Eth Zürich, Department Of Computer Science, Zürich, 8092, Switzerland
5.Pazhou Lab, Guangzhou, 510335, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Tang, Lulu,Chen, Ke,Wu, Chaozheng,et al. Improving Semantic Analysis on Point Clouds via Auxiliary Supervision of Local Geometric Priors[J]. IEEE Transactions on Cybernetics, 2022, 52(6), 4949-4959.
APA Tang, Lulu., Chen, Ke., Wu, Chaozheng., Hong, Yu., Jia, Kui., & Yang, Zhi Xin (2022). Improving Semantic Analysis on Point Clouds via Auxiliary Supervision of Local Geometric Priors. IEEE Transactions on Cybernetics, 52(6), 4949-4959.
MLA Tang, Lulu,et al."Improving Semantic Analysis on Point Clouds via Auxiliary Supervision of Local Geometric Priors".IEEE Transactions on Cybernetics 52.6(2022):4949-4959.
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