Unsupervised Region Attention Network for Person Re-Identification

Unsupervised Region Attention Network for Person Re-Identification

As supervised person re-identification (Re-Id) requires massive labeled pedestrian data and it is very difficult to collect sufficient labeled data in reality, unsupervised Re-Id approaches attract much more attention than the former. Existing unsupervised person Re-Id models learn global features o...

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Bibliographic Details
Main Authors: Chenrui Zhang, Yangxu Wu, Tao Lei
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Unsupervised person re-identification
region attention
first neighbor relation
occlusion
pose variant
Online Access:https://ieeexplore.ieee.org/document/8897584/

Internet

https://ieeexplore.ieee.org/document/8897584/

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