Training approach using the shallow model and hard triplet mining for person re‐identification
Author:
Affiliation:
1. The School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology123 Cheomdangwagi‐ro, Buk‐guGwangju61005Republic of Korea
2. Engineering and Applied ScienceUniversity of ReginaSaskatchewanCanada
Funder
Institute for Information and Communications Technology Promotion
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2019.0334
Reference54 articles.
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3. 2010 2010 IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) San Francisco USA M. Farenzena L. Bazzani A. Perina Person reidentification by symmetry‐driven accumulation of local features 2360 2367
4. 2012 2012 Sixth Int. Conf. on Distributed Smart Cameras (ICDSC) Hong Kong M. Bredereck X. Jiang M. Körner Data association for multiobject tracking‐by‐detection in multi‐camera networks 1 6
5. Collaborative pedestrian tracking and data fusion with multiple cameras;Lin D.T.;IEEE Trans. Inf. Forensics Sec.,2011
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