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http://bura.brunel.ac.uk/handle/2438/26708Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jin, Z | - |
| dc.contributor.author | Wang, Y | - |
| dc.contributor.author | Wang, Q | - |
| dc.contributor.author | Shen, Y | - |
| dc.contributor.author | Meng, H | - |
| dc.date.accessioned | 2023-06-21T12:45:41Z | - |
| dc.date.available | 2023-06-21T12:45:41Z | - |
| dc.date.issued | 2023-06-09 | - |
| dc.identifier | ORCID iDs: Qicong Wang https://orcid.org/0000-0001-7324-0433; Yehu Shen https://orcid.org/0000-0002-8917-719X; Hongying Meng https://orcid.org/0000-0002-8836-1382 | - |
| dc.identifier.citation | Jin, Z. et al. (2023) 'SSRL: Self-supervised Spatial-temporal Representation Learning for 3D Action recognition, IEEE Transactions on Circuits and Systems for Video Technology, 2023, pp. 1 - 13. doi: 10.1109/tcsvt.2023.3284493. | en_US |
| dc.identifier.issn | 1051-8215 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/26708 | - |
| dc.description.sponsorship | Shenzhen Science and Technology Program (Grant Number: JCYJ20200109143035495); 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 51975394). | en_US |
| dc.format.extent | 1 - 13 | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
| dc.rights | Copyright © 2023 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works by sending a request to pubs-permissions@ieee.org. For more information, see https://www.ieee.org/publications/rights/rights-policies.html | - |
| dc.rights.uri | https://www.ieee.org/publications/rights/rights-policies.html | - |
| dc.subject | self-supervised learning | en_US |
| dc.subject | contrastive learning | en_US |
| dc.subject | skeleton action recognition | en_US |
| dc.title | SSRL: Self-supervised Spatial-temporal Representation Learning for 3D Action recognition | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | https://doi.org/10.1109/tcsvt.2023.3284493 | - |
| dc.relation.isPartOf | IEEE Transactions on Circuits and Systems for Video Technology | - |
| pubs.publication-status | Published | - |
| pubs.volume | 0 | - |
| dc.identifier.eissn | 1558-2205 | - |
| dc.rights.holder | Institute of Electrical and Electronics Engineers (IEEE) | - |
| Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © 2023 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works by sending a request to pubs-permissions@ieee.org. For more information, see https://www.ieee.org/publications/rights/rights-policies.html | 21.75 MB | Adobe PDF | View/Open |
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