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Revisiting Jump-Diffusion Process for Visual Tracking: A Reinforcement Learning Approach

  • Published:2019-08 Issue:8 Volume:29 Page:2431-2441
  • ISSN:1051-8215
  • Container-title:IEEE Transactions on Circuits and Systems for Video Technology
  • language:
  • Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Liu XiaobaiORCID,Xu Qian,Chau Thuan,Mu YadongORCID,Zhu LeiORCID,Yan Shuicheng

Funder

NJUST Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information

Beijing Municipal Science and Technology Commission

Defense Advanced Research Projects Agency

National Science Foundation

ONR

San Diego State University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Cited by 10 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. The use of reinforcement learning algorithms in object tracking: A systematic literature review;Neurocomputing;2024-09

2. Dynamic Graph Learning for Data Clustering;Dynamic Graph Learning for Dimension Reduction and Data Clustering;2023-09-21

3. Semantic Boundary Detection With Reinforcement Learning for Continuous Sign Language Recognition;IEEE Transactions on Circuits and Systems for Video Technology;2021-03

4. Deep Reinforcement Learning Techniques in Diversified Domains: A Survey;Archives of Computational Methods in Engineering;2021-02-10

5. On the Use of Deep Reinforcement Learning for Visual Tracking: A Survey;IEEE Access;2021
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