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Dual-Branch Network Fused with Attention Mechanism for Clothes-Changing Person Re-identification

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Artificial Intelligence and Mobile Services – AIMS 2022 (AIMS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13729))

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Abstract

Clothes-changing person re-identification is a hot issue in the current academic circle. The key to this work is to extract the inherent characteristics of people, such as gait and body shape. Most of the current methods assume that persons’ clothes will not change in a short period of time, so these methods are not applicable when changing clothes. Based on this situation, this paper proposes a dual-branch network clothes-changing person re-identification method fused with attention mechanism. The attention mechanism captures and aggregates persons semantic-related information in channels and spaces, and trains the clothes classification branch to suppress Sensitivity of the network to clothing features. In addition, the method in this paper does not use auxiliary means such as human skeleton, and the complexity of the model is greatly reduced. This paper conducts experiments on the popular clothes-changing person re-identification dataset PRCC, and the experimental results show that the method in this paper is more advanced than popular methods. This paper also conducts experiments on LaST, an ultra-large-scale cross-space-time dataset, and also achieves competitive result results.

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Authors and Affiliations

  1. Minzu University of China, Beijing, 100190, China

    Yong Lu & Mingzhe Jin

Authors
  1. Yong Lu
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  2. Mingzhe Jin
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Corresponding author

Correspondence to Yong Lu .

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Editors and Affiliations

  1. Minzu University of China, Beijing, China

    Xiuqin Pan

  2. Hainan University, Haikou, China

    Ting Jin

  3. Kingdee International Software Group Co., Ltd., Shenzhen, China

    Liang-Jie Zhang

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Lu, Y., Jin, M. (2022). Dual-Branch Network Fused with Attention Mechanism for Clothes-Changing Person Re-identification. In: Pan, X., Jin, T., Zhang, LJ. (eds) Artificial Intelligence and Mobile Services – AIMS 2022. AIMS 2022. Lecture Notes in Computer Science, vol 13729. Springer, Cham. https://doi.org/10.1007/978-3-031-23504-7_9

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  • DOI: https://doi.org/10.1007/978-3-031-23504-7_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23503-0

  • Online ISBN: 978-3-031-23504-7

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