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Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/25523Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Wang, P | - |
| dc.contributor.author | Su, F | - |
| dc.contributor.author | Zhao, Z | - |
| dc.contributor.author | Zhao, Y | - |
| dc.contributor.author | Boulgouris, NV | - |
| dc.date.accessioned | 2022-11-22T20:27:24Z | - |
| dc.date.available | 2022-11-22T20:27:24Z | - |
| dc.date.issued | 2022-10-05 | - |
| dc.identifier | ORCID iDs: Pingyu Wang https://orcid.org/0000-0001-9769-8035; Fei Su https://orcid.org/0000-0003-4245-4687; Zhicheng Zhao https://orcid.org/0000-0001-6506-7298; Nikolaos Boulgouris https://orcid.org/0000-0002-5382-6856. | - |
| dc.identifier.citation | Wang, P. et al. (2022) 'GAReID: Grouped and Attentive High-Order Representation Learning for Person Re-Identification', IEEE Transactions on Neural Networks and Learning Systems, 0 (in press), pp. 1 - 15. doi: 10.1109/tnnls.2022.3209537. | en_US |
| dc.identifier.issn | 2162-237X | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/25523 | - |
| dc.description.sponsorship | 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62076033 and U1931202) | en_US |
| dc.format.extent | 1 - 15 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
| dc.rights | Copyright © 2022 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. | - |
| dc.rights.uri | https://www.ieee.org/publications/rights/rights-policies.html | - |
| dc.subject | group shuffle | en_US |
| dc.subject | high-order pooling | en_US |
| dc.subject | Kronecker product | en_US |
| dc.subject | part misalignments | en_US |
| dc.subject | person re-identification (ReID) | en_US |
| dc.title | GAReID: Grouped and Attentive High-Order Representation Learning for Person Re-Identification | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | https://doi.org/10.1109/tnnls.2022.3209537 | - |
| dc.relation.isPartOf | IEEE Transactions on Neural Networks and Learning Systems | - |
| pubs.publication-status | Published | - |
| pubs.volume | 0 | - |
| dc.identifier.eissn | 2162-2388 | - |
| 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 © 2022 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. | 7.06 MB | Adobe PDF | View/Open |
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