Occluded Person Re-Identification via Defending Against Attacks From Obstacles-Reference-Cited by-同舟云学术

Occluded Person Re-Identification via Defending Against Attacks From Obstacles

Published:2023 Issue: Volume:18 Page:147-161
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Wang Shujuan¹,Liu Run¹^ORCID,Li Huafeng¹^ORCID,Qi Guanqiu²^ORCID,Yu Zhengtao¹^ORCID

Affiliation:

1. Yunnan Provincial Key Laboratory of Artificial Intelligence, Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China

2. Computer Information Systems Department, State University of New York at Buffalo State, Buffalo, NY, USA

Funder

National Natural Science Foundation of China

National Key Research and Development Plan Project

Yunnan Natural Science Funds

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/10206/9970396/09933492.pdf?arnumber=9933492

Reference67 articles.

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4. Divergence-agnostic Unsupervised Domain Adaptation by Adversarial Attacks

5. Multi-Expert Adversarial Attack Detection in Person Re-identification Using Context Inconsistency

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