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Volume 169, Issue CJan 2024
Reflects downloads up to 07 Dec 2024Bibliometrics
editorial
announcement
announcement
research-article
Asymmetric double networks mutual teaching for unsupervised person Re-identification
Highlights

  • The ADNMT uses two asymmetric networks to generate pseudo-labels for each other by clustering and iterative training.
  • Based on alternate training and mutual teaching to optimize the pseudo-labels.
  • The SCIC compensates the ...

Abstract

Unsupervised person re-identification (Re-ID) has always been challenging in computer vision. It has received much attention from researchers because it does not require any labeled information and can be freely deployed to new scenarios. Most ...

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