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CALTracker: Cross-Task Association Learning for Multiple Object Tracking

  • Published:2023 Issue: Volume:30 Page:1622-1626
  • ISSN:1070-9908
  • Container-title:IEEE Signal Processing Letters
  • language:
  • Short-container-title:IEEE Signal Process. Lett.

Author:

Liu Jialin1ORCID,Kong Jun1ORCID,Jiang Min2ORCID,Liu Tianshan3ORCID

Affiliation:

1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China

2. Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence, Jiangnan University, Wuxi, China

3. Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong, China

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

China Postdoctoral Science Foundation

111 Projects

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Igtracker: task and instance information gaps in multiple object tracking;International Journal of Machine Learning and Cybernetics;2024-05-02
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