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A Comprehensive Review of Deep Learning-Based Visual Multi-Object Tracking
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Yong LI1, 2, Fang LIN1, 3, Yu-ang CHEN1, 3, Shu-han LÜ1, 3
Science Technology and Engineering | 2025, 25(22) : 9211 - 9223
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Science Technology and Engineering | 2025, 25(22): 9211-9223
• Surveies·Automation and Computational Technology •
A Comprehensive Review of Deep Learning-Based Visual Multi-Object Tracking
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Yong LI1, 2, Fang LIN1, 3, Yu-ang CHEN1, 3, Shu-han LÜ1, 3
Affiliations
  • 1 Key Laboratory of Counter-Terrorism Command & Information Engineering, Ministry of Education, Engineering University of PAP, Xi’an 710086, China
  • 2 College of Information Engineering, Engineering University of PAP, Xi’an 710086, China
  • 3 Graduate Student Brigade, Engineering University of PAP, Xi’an 710086, China
Published: 2025-08-08 doi: 10.12404/j.issn.1671-1815.2409394
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Multi-object tracking is an important branch in the field of computer vision. Owing to the rapid development of computer hardware and deep learning technology, significant progress has been made in deep learning-based multi-object tracking, yielding remarkable results. To promote the research progress in the field of visual multi-object tracking, a comprehensive review of recent innovative outcomes was conducted to discuss the current state of research advancements.On the basis of introducing the background and application scenarios of multi-object tracking, the research progress was discussed in four aspects: tracking by detection,joint detecting and tracking,transformer-based tracking,referring multi-object tracking. Common benchmark datasets and evaluation metrics for multi-tracking algorithms were summarized, and a comparative analysis of the algorithms mentioned was conducted on these datasets. Ultimately, exploring the prospective evolution of deep learning-based visual multi-object tracking, three future research directions were proposed for scholars actively engaged in this field.

deep learning  /  multi-object tracking  /  computer vision  /  Transformer
Yong LI, Fang LIN, Yu-ang CHEN, Shu-han LÜ. A Comprehensive Review of Deep Learning-Based Visual Multi-Object Tracking[J]. Science Technology and Engineering, 2025 , 25 (22) : 9211 -9223 . DOI: 10.12404/j.issn.1671-1815.2409394
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Year 2025 volume 25 Issue 22
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Article Info
doi: 10.12404/j.issn.1671-1815.2409394
  • Receive Date：2024-12-18
  • Online Date：2026-02-11
  • Published：2025-08-08
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History
  • Received：2024-12-18
  • Revised：2025-04-17
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Affiliations
    1 Key Laboratory of Counter-Terrorism Command & Information Engineering, Ministry of Education, Engineering University of PAP, Xi’an 710086, China
    2 College of Information Engineering, Engineering University of PAP, Xi’an 710086, China
    3 Graduate Student Brigade, Engineering University of PAP, Xi’an 710086, China
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