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Multi-task Learning for Person Re-identification

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Intelligence Science and Big Data Engineering (IScIDE 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10559))

Abstract

Person re-identification is a hot topic due to its huge application potentials. Siamese network is a good method to learn feature representation in verification tasks and has been used in previous person re-identification research, but hard to convergence during training process. This paper presents a multi-task learning pipeline including Siamese loss for learning deep feature representations of people appearance. Firstly, we point out the defects of training a convolutional neural network (CNN) only with Siamese loss which is usually used for person re-identification. Secondly, a multi-task CNN for person re-identification combing the Softmax loss with Siameses loss is proposed. Finally, some experiments are carried out to test the performance of proposed multi-task person appearance learning pipeline. Experiments on various pedestrian dataset shows the effectiveness of our pipeline. Our method outperforms state-of-the-art person re-identification methods in some public datasets.

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Acknowledgements

A project supported by Scientific Research Fund of Zhejiang Provincial Education Department (Grant No. Y201534841); Supported by National Natural Science Foundation of China (Grant No. 61503338) and Natural Science Foundation of Zhejiang Province (Grant No. LQ15F030005).

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Authors and Affiliations

  1. College of Computer Science, Zhejiang University of Technology, 288 Liuhe Road, West Lake District, 310023, Hangzhou City, China

    Hua Gao, Yujiao Huang, Yiwei Dong & Sixian Chan

  2. School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology Zijin College, 89 Wenlan Road, Qixia District, 210023, Nanjing City, China

    Lingyan Yu

Authors
  1. Hua Gao
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  2. Lingyan Yu
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  3. Yujiao Huang
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  4. Yiwei Dong
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  5. Sixian Chan
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Corresponding author

Correspondence to Hua Gao .

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Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Yi Sun

  2. Dalian University of Technology, Dalian, China

    Huchuan Lu

  3. Dalian University of Technology, Dalian, China

    Lihe Zhang

  4. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  5. Beijing Institute of Technology, Beijing, China

    Hua Huang

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Gao, H., Yu, L., Huang, Y., Dong, Y., Chan, S. (2017). Multi-task Learning for Person Re-identification. In: Sun, Y., Lu, H., Zhang, L., Yang, J., Huang, H. (eds) Intelligence Science and Big Data Engineering. IScIDE 2017. Lecture Notes in Computer Science(), vol 10559. Springer, Cham. https://doi.org/10.1007/978-3-319-67777-4_23

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  • DOI: https://doi.org/10.1007/978-3-319-67777-4_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67776-7

  • Online ISBN: 978-3-319-67777-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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