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International Conference on Image and Graphics

ICIG 2021: Image and Graphics pp 314–325Cite as

Attention-Guided Siamese Network for Clothes-Changing Person Re-identification

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12889))

Abstract

Person re-identification (re-id) has achieved significant progresses in recent years. However, the existing methods generally assume that the clothes of pedestrians remain unchanged throughout the surveillance periods, which is contradict to realistic environment where pedestrians may change their clothes. Current re-id techniques may encounter a dramatic performance degradation when the pedestrians change the clothes. In this paper, we propose a novel attention-guided siamese network (AGS-Net) to solve the cross-clothes re-id challenge. The AGS-Net integrates the visual and contour information together by developing a dual-branch structure, among which one extracts powerful features from raw inputs while the other learns robust features from the sketch image. Moreover, we exploit the attention modules to emphasize reliable identity-related features considering changing clothes and avoid generating features sensitive to clothes. Specifically, we propose a clothes-change invariant constraint to learn clothes-invariant features. Experimental results verify the effectiveness of our approach.

This project was supported by Natural Science Foundation of China (61902444, 62076258).

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China

    Zhanxiang Feng, Sien Huang & Jianhuang Lai

  2. Guangzhou Xinhua University, Guangzhou, China

    Jianhuang Lai

  3. Guangdong Province Key Laboratory of Information Security Technology, Guangzhou, China

    Jianhuang Lai

  4. Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, Guangzhou, China

    Jianhuang Lai

Authors
  1. Zhanxiang Feng
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  2. Sien Huang
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  3. Jianhuang Lai
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Corresponding author

Correspondence to Jianhuang Lai .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Yuxin Peng

  2. Tsinghua University, Beijing, China

    Shi-Min Hu

  3. Tampere University, Tampere, Finland

    Moncef Gabbouj

  4. Zhejiang University, Hangzhou, China

    Kun Zhou

  5. Technion – Israel Institute of Technology, Haifa, Israel

    Michael Elad

  6. Tsinghua University, Beijing, China

    Kun Xu

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Feng, Z., Huang, S., Lai, J. (2021). Attention-Guided Siamese Network for Clothes-Changing Person Re-identification. In: Peng, Y., Hu, SM., Gabbouj, M., Zhou, K., Elad, M., Xu, K. (eds) Image and Graphics. ICIG 2021. Lecture Notes in Computer Science(), vol 12889. Springer, Cham. https://doi.org/10.1007/978-3-030-87358-5_25

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  • DOI: https://doi.org/10.1007/978-3-030-87358-5_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87357-8

  • Online ISBN: 978-3-030-87358-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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