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Chinese Conference on Pattern Recognition and Computer Vision (PRCV)

PRCV 2022: Pattern Recognition and Computer Vision pp 646–658Cite as

Dual-Branch Memory Network for Visual Object Tracking

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13537))

Abstract

In recent years, memory-based tracking has become the focus of visual object tracking due to its robustness toward objects with arbitrary forms. Although advanced memory networks have produced excellent results, balancing long-term and short-term memory remains a difficult problem in memory building. Therefore, we propose the dual-branch memory network (DualMN), which divided the memory-building task into long-term and short-term memory-building tasks, avoiding conflict between them skillfully. Specifically, the DualMN consists of a long-term memory branch and a short-term memory branch. The former is dedicated to learning the difference between the new target appearance and the surrounding environment. The latter focuses on learning the essential feature of the target to prevent the target drift. In the tracking process, the long-term memory branch and the short-term memory branch complement each other to achieve more accurate target positioning. Experiments results on OTB2015, NFS, UAV123, LaSOT, and TrackingNet benchmarks show that our DualMN achieves comparable performance to the advanced trackers.

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Author information

Authors and Affiliations

  1. College of Software Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, China

    Jingchao Wang, Jianwei Zhang & Mengen Miao

  2. College of Electric and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, China

    Huanlong Zhang & Jiapeng Zhang

  3. Henan Key Laboratory of Data Intelligence on Food Safety, Zhengzhou, 450000, China

    Jingchao Wang, Jianwei Zhang & Mengen Miao

Authors
  1. Jingchao Wang
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  2. Huanlong Zhang
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  3. Jianwei Zhang
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  4. Mengen Miao
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  5. Jiapeng Zhang
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Corresponding author

Correspondence to Jianwei Zhang .

Editor information

Editors and Affiliations

  1. Southern University of Science and Technology, Shenzhen, China

    Shiqi Yu

  2. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Zhaoxiang Zhang

  3. Hong Kong Baptist University, Hong Kong, China

    Pong C. Yuen

  4. Northwestern Polytechnical University, Xi'an, China

    Junwei Han

  5. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  6. Hong Kong Baptist University, Hong Kong, China

    Yike Guo

  7. Sun Yat-sen University, Guangzhou, China

    Jianhuang Lai

  8. Southern University of Science and Technology, Shenzhen, China

    Jianguo Zhang

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Cite this paper

Wang, J., Zhang, H., Zhang, J., Miao, M., Zhang, J. (2022). Dual-Branch Memory Network for Visual Object Tracking. In: Yu, S., et al. Pattern Recognition and Computer Vision. PRCV 2022. Lecture Notes in Computer Science, vol 13537. Springer, Cham. https://doi.org/10.1007/978-3-031-18916-6_51

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  • DOI: https://doi.org/10.1007/978-3-031-18916-6_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-18915-9

  • Online ISBN: 978-3-031-18916-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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