Tri-Invariance Contrastive Framework for Robust Unsupervised Person Re-Identification

Unsupervised person re-identification (Re-ID) has been proven very effective and it boosts the performance in learning representations from unlabeled data in the dataset. Most current methods have good accuracy, but there are two main problems. First, clustering often generates noisy labels. Second,...

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Autors principals:	Lei Wang, Chengang Liu, Xiaoxiao Wang, Weidong Gao, Xuejian Ge, Shunjie Zhu
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2025-11-01
Col·lecció:	Mathematics
Matèries:	person reidentification contrastive learning unsupervised learning robust modeling
Accés en línia:	https://www.mdpi.com/2227-7390/13/21/3570
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