Exponential Information Bottleneck Theory Against Intra-Attribute Variations for Pedestrian Attribute Recognition-Reference-Cited by-同舟云学术

Exponential Information Bottleneck Theory Against Intra-Attribute Variations for Pedestrian Attribute Recognition

Published:2023 Issue: Volume:18 Page:5623-5635
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Wu Junyi¹^ORCID,Huang Yan²^ORCID,Gao Min³,Gao Zhipeng¹,Zhao Jianqiang¹,Shi Jieming⁴^ORCID,Zhang Anguo⁴^ORCID

Affiliation:

1. AI Research Center, Xiamen Meiya Pico Information Company Ltd., Xiamen, China

2. Center for Research on Intelligent Perception and Computing (CRIPAC), National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China

3. Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China

4. Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

Funder

National Natural Science Foundation of China

Fellowship of China Post-Doctoral Science Foundation

International Post-Doctoral Exchange Fellowship Program (Talent-Introduction Program) of China

Special Research Assistant Program of the Chinese Academy of Sciences

Public Security Artificial Intelligence Infrastructure Support Platform

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

http://xplorestaging.ieee.org/ielx7/10206/9970396/10238746.pdf?arnumber=10238746

Reference60 articles.

1. Densely Connected Convolutional Networks

2. Recurrent Attention Model for Pedestrian Attribute Recognition

3. Adaptively Weighted Multi-task Deep Network for Person Attribute Classification

4. Grouping Attribute Recognition for Pedestrian with Joint Recurrent Learning

5. End-to-End Domain Adaptive Attention Network for Cross-Domain Person Re-Identification

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