AttMOT: Improving Multiple-Object Tracking by Introducing Auxiliary Pedestrian Attributes-Reference-Cited by-同舟云学术

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AttMOT: Improving Multiple-Object Tracking by Introducing Auxiliary Pedestrian Attributes

Published:2024 Issue: Volume: Page:1-15
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Li Yunhao¹^ORCID,Xiao Zhen²,Yang Lin³,Meng Dan⁴^ORCID,Zhou Xin²,Fan Heng⁵^ORCID,Zhang Libo²^ORCID

Affiliation:

1. School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China

2. Institute of Software, State Key Laboratory of Computer Science, Chinese Academy of Sciences, Beijing, China

3. Turing Quantum Company, Beijing, China

4. OPPO Research Institute, Beijing, China

5. Department of Computer Science and Engineering, University of North Texas, Denton, TX, USA

Funder

Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences

Youth Innovation Promotion Association, Chinese Academy of Science

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10508509.pdf?arnumber=10508509

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