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 …

Multi-view clustering has become a rapidly growing field in machine learning and data
mining areas by combining useful information from different views for last decades. Although …

Multi-view clustering usually attempts to improve the final performance by integrating graph
structure information from different views and methods based on anchor are presented to …

Multi-view clustering aims to study the complementary information across views and
discover the underlying structure. For solving the relatively high computational cost for the …

In recent years, subspace clustering (SC) methods have been widely used in machine
learning and computer vision. However, the self-expressive matrix obtained by the existing …

Multiview clustering (MVC) has been widely studied in machine learning and data mining for
its capability of improving clustering performance by fusing the information from multiview …

In this paper, we study a challenging problem in contrastive learning when just a portion of
data is aligned in multi-view dataset due to temporal, spatial, or spatio-temporal …

Multi-view clustering methods have been extensively explored in the last decades. This kind
of methods is built on the assumption that the data are sampled from multiple subspaces …

Tensor-based multi-view clustering has recently received significant attention due to its
exceptional ability to explore cross-view high-order correlations. However, most existing …

Subspace clustering methods, employing sparse and low-rank models, have demonstrated
efficacy in clustering high-dimensional data. These approaches typically assume the …