Self-Supervised Recovery and Guide for Low-Resolution Person Re-Identification-Reference-Cited by-同舟云学术

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Self-Supervised Recovery and Guide for Low-Resolution Person Re-Identification

Published:2024 Issue: Volume:19 Page:6252-6263
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Han Ke¹^ORCID,Huang Yan²^ORCID,Wang Liang²^ORCID,Liu Zikun³^ORCID

Affiliation:

1. School of Future Technology, University of Chinese Academy of Sciences (UCAS), Beijing, China

2. CRIPAC, NLPR, CASIA, Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), and the School of Artificial Intelligence, UCAS, Beijing, China

3. Samsung Research China-Beijing (SRC-B), Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/10206/10319981/10547053.pdf?arnumber=10547053

Reference46 articles.

1. Deep Low-Resolution Person Re-Identification

2. Cascaded SR-GAN for Scale-Adaptive Low Resolution Person Re-identification

3. Inter-Task Association Critic for Cross-Resolution Person Re-Identification

4. Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification

5. Cross-resolution adversarial dual network for person re-identification and beyond;Li;arXiv:2002.09274,2020

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