Spatial-temporal graph-guided global attention network for video-based person re-identification-Reference-Cited by-同舟云学术

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Spatial-temporal graph-guided global attention network for video-based person re-identification

Published:2023-12-03 Issue:1 Volume:35 Page:
ISSN:0932-8092
Container-title:Machine Vision and Applications
language:en
Short-container-title:Machine Vision and Applications

Author:

Li Xiaobao,Wang Wen,Li Qingyong,Zhang Jiang

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://link.springer.com/content/pdf/10.1007/s00138-023-01489-w.pdf

Reference70 articles.

1. Karanam, S., Gou, M., Wu, Z., Rates-Borras, A., Camps, O.I., Radke, R.J.: A systematic evaluation and benchmark for person re-identification: features, metrics, and datasets. IEEE Trans. Pattern Anal. Mach. Intell. 41(3), 523–536 (2019)

2. Ye, M., Shen, J., Lin, G., Xiang, T., Shao, L., Hoi, S.C.: Deep learning for person re-identification: a survey and outlook. IEEE Trans. Pattern Anal. Mach. Intell. 44(6), 2872–2893 (2021)

3. Sun, J., Li, Y., Chen, H., Peng, Y., Zhu, J.: Visible-infrared person re-identification model based on feature consistency and modal indistinguishability. Mach. Vis. Appl. 34(1), 14 (2023)

4. Perwaiz, N., Shahzad, M., Fraz, M.: Ubiquitous vision of transformers for person re-identification. Mach. Vis. Appl. 34(2), 27–40 (2023)

5. Felzenszwalb, P.F., Girshick, R.B., McAllester, D., Ramanan, D.: Object detection with discriminatively trained part-based models. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1627–1645 (2010)

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