Exploring Latent Information for Unsupervised Person Re-Identification by Discriminative Learning Networks

Exploring Latent Information for Unsupervised Person Re-Identification by Discriminative Learning Networks

For unsupervised domain adaption in person re-identification (Re-ID) tasks, the generally used label estimation approaches simply use the global features or the uniform part features. They often neglect the variations of samples having the same identity caused by occlusion, misalignment and uncontro...

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Bibliographic Details
Main Authors: Hongwei Ge, Kai Zhang, Liang Sun, Guozhen Tan
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Person re-identification
unsupervised domain adaptation
unsupervised learning
Online Access:https://ieeexplore.ieee.org/document/9024018/

Internet

https://ieeexplore.ieee.org/document/9024018/

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