Data-driven pedestrian re-identification based on hierarchical semantic representation

Author:

Cheng Keyang1ORCID,Xu Fangjie1,Tao Fei1,Qi Man2,Li Maozhen3

Affiliation:

1. School of Computer Science and Communication Engineering; Jiangsu University; Zhenjiang 212013 China

2. School of Law, Criminal Justice and Computing; Canterbury Christ Church University; Canterbury CT1 1QU UK

3. School of Engineering and Design; Brunei University; Uxbridge London UB8 3PH UK

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province of China

International Postdoctoral Exchange Fellowship Program

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference70 articles.

1. Cheng L Research on Key Technology of Person Re-Identification [PhD thesis] Beijing, China Beijing University of Posts and Telecommunications 2013

2. Farenzena M Bazzani L Perina A Murino V Cristani M Person re-identification by symmetry-driven accumulation of local features 2010 San Francisco, CA

3. Person re-identification based on multi-salience fusion;Huo;Opto-Electronic Eng,2015

4. Zhao R Ouyang W Wang X Unsupervised salience learning for person re-identification 2013 Portland, OR

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