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International Conference on Image and Graphics

ICIG 2021: Image and Graphics pp 326–337Cite as

Cross-domain Person Re-identification Based on the Sample Relation Guidance

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

Abstract

The existing mainstream cross-domain person re-identification (Re-ID) methods mainly focus on reducing the deviation of the generated pseudo labels, and they did not introduce veracious label information for algorithm training on the unlabeled target domain. In this paper, we propose a new sample relation guidance (SRG) method. Specifically, the sample relation is a real label, which represents a definite positive sample pairs’ relation or negative sample pairs’ relation. Here, we construct a triple-branch network to form sample relation labels to improve the expressive power of features. In addition, the potential relationship of target domain label loss and source domain label loss is explored, and an adaptive adjustment label loss (ADLL) method is proposed, which effectively improves the generalization performance of the model. Extensive experiments over three benchmarks proved that our method outperforms the state-of-the-art methods.

Supported in part by the National Natural Science Foundation of China under Grant 61872034, 62062021, 61972030, and 62011530042, in part by the Beijing Municipal Natural Science Foundation under Grant 4202055, in part by the Natural Science Foundation of Guizhou Province under Grant [2019]1064.

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Author information

Authors and Affiliations

  1. Beijing Jiaotong University, Beijing, China

    Yue Zhang, Fanghui Zhang, Shichao Kan, Jiaping Zong & Yigang Cen

  2. Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China

    Yue Zhang, Fanghui Zhang, Shichao Kan, Jiaping Zong & Yigang Cen

  3. School of Mechanical engineering, Guizhou University, Guiyang, China

    Linna Zhang

Authors
  1. Yue Zhang
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  2. Fanghui Zhang
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  3. Shichao Kan
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  4. Linna Zhang
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  5. Jiaping Zong
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  6. Yigang Cen
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Corresponding author

Correspondence to Yigang Cen .

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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Cite this paper

Zhang, Y., Zhang, F., Kan, S., Zhang, L., Zong, J., Cen, Y. (2021). Cross-domain Person Re-identification Based on the Sample Relation Guidance. 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_26

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  • DOI: https://doi.org/10.1007/978-3-030-87358-5_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87357-8

  • Online ISBN: 978-3-030-87358-5

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