Thanks for the cross-modal retrieval techniques, visible-infrared (RGB-IR) person re-
identification (Re-ID) is achieved by projecting them into a common space, allowing person …

Domain adaptation person re-identification (Re-ID) is a challenging task, which aims to
transfer the knowledge learned from the labeled source domain to the unlabeled target …

Due to the scarcity of manually annotated data required for fine-grained video
understanding, few-shot fine-grained (FS-FG) action recognition has gained significant …

Abstract Re-identification (Re-ID) is a process that seeks to identify concern individuals from
successive non-overlap** photographs. The area of computer vision has recently seen an …

Person re-identification (Re-ID) aims to retrieve a particular pedestrian's identification from a
surveillance system consisting of non-overlap** cameras. In recent years, researchers …

Although existing domain-adaptive person re-identification (re-ID) methods have achieved
competitive per-formance, most of them highly rely on the reliability of pseudo-label …

Unsupervised domain adaptation (UDA) in person re-identification (re-ID) is a challenging
task, aiming to learn a model with labeled source data and unlabeled target data to …

Unsupervised domain adaptation (UDA) techniques for person re-identification (ReID) have
been extensively studied to facilitate the transfer of knowledge from labeled source domains …

Abstract Generalized Person Re-Identification (GReID) aims to develop a model capable of
robust generalization across unseen target domains, even with training on a limited set of …

Despite not being designed for this purpose, the use of variational autoencoders (VAEs) has
proven remarkably effective for disentangled representation learning (DRL). Recent …