Visible-infrared cross-modality person re-identification (VI-ReID) is currently a prevalent but
challenging research topic in computer vision, since it can remedy the poor performance of …

For the visible-infrared person re-identification (VIReID) task, one of the major challenges is
the modality gaps between visible (VIS) and infrared (IR) images. However, the training …

In this article, we propose a unified framework to solve the following two challenging
problems in incomplete multi-view representation learning: i) how to learn a consistent …

In the evolving landscape of surveillance and security applications, the task of person re-
identification (re-ID) has significant importance, but also presents notable difficulties. This …

Multiview clustering (MVC) aims to reveal the underlying structure of multiview data by
categorizing data samples into clusters. Deep learning-based methods exhibit strong feature …

Unsupervised visible-infrared person re-identification is a challenging task due to the large
modality gap and the unavailability of cross-modality correspondences. Cross-modality …

Text-to-image person re-identification (TIReID) is a compelling topic in the cross-modal
community which aims to retrieve the target person based on a textual query. Although …

Deep multi-view clustering leverages deep neural networks to achieve promising
performance, but almost all existing methods implicitly assume that all views are aligned …

In recent, some robust contrastive multi-view clustering (MvC) methods have been
proposed, which construct data pairs from neighborhoods to alleviate the false negative …