Global relational attention with a maximum suppression constraint for vehicle re-identification-Reference-Cited by-同舟云学术

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Global relational attention with a maximum suppression constraint for vehicle re-identification

Published:2023-10-25 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Pang Xiyu,Yin Yilong^ORCID,Tian Xin

Funder

National Natural Science Foundation of China

Major Basic Research Project of the Natural Science Foundation of Shandong Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-023-01993-5.pdf

Reference68 articles.

1. Chen B, Deng W, Hu J (2019) Mixed high-order attention network for person re-identification. In: ICCV, pp 371–381

2. Xu J, Zhao R, Zhu F, Wang H, Ouyang W (2018) Attention-aware compositional network for person re-identification. In: CVPR, pp 2119–2128

3. Fang P, Zhou J, Roy SK, Petersson L, Harandi M (2019) Bilinear attention networks for person retrieval. In: ICCV, pp 8030–8039

4. Zhang Z, Lan C, Zeng W, Xin J, Zhibo C (2020) Relation-aware global attention for person re-identification. In: CVPR, pp 3183–3192

5. Wang G, Yuan Y, Chen X, Li J, Zhou X (2018) Learning discriminative features with multiple granularities for person re-identification. In: Proceedings of the 26th ACM international conference on multimedia, October, pp 274–282

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