Unsupervised Person Re-Identification with Attention-Guided Fine-Grained Features and Symmetric Contrast Learning

Unsupervised person re-identification has attracted a lot of attention due to its strong potential to adapt to new environments without manual annotation, but learning to recognise features in disjoint camera views without annotation is still challenging. Existing studies tend to ignore the optimisa...

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Detalles Bibliográficos
Autores principales: Wu, Yongzhi, Yang, Wenzhong, Wang, Mengting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503568/
https://www.ncbi.nlm.nih.gov/pubmed/36146326
http://dx.doi.org/10.3390/s22186978

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503568/
https://www.ncbi.nlm.nih.gov/pubmed/36146326
http://dx.doi.org/10.3390/s22186978

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