In recent several years the information bottleneck (IB) principle provides an information-
theoretic framework for deep multi-view clustering (MVC) by compressing multi-view …

Multi-view action clustering leverages the complementary information from different camera
views to enhance the clustering performance. Although existing approaches have achieved …

The widely adopted Jacobi-Fourier moment (JFM) is limited by its inability to effectively
capture spatial information. Although fractional-order JFM (FOJFM) introduces spatial …

Video summarization (VS) technologies can automatically extract key frames with effective
information and thus can help to quickly identify the events or speed up the decision-making …

Crowd path planning aims to find the optimal path between the source and destination for
multiple agents in crowd scenes. The advent of parallel theory and digital twin technologies …

Contrastive multi-view clustering is widely recognized for its effectiveness in mining feature
representation across views via contrastive learning (CL), gaining significant attention in …

Self-supervised clustering has garnered widespread attention due to its ability to discover
latent clustering structures without the need for external labels. However, most existing …

Contrastive graph clustering (CGC) has become a prominent method for self-supervised
representation learning by contrasting augmented graph data pairs. However, the …

Multiview clustering (MVC) provides a natural formulation to generate clusters for multiview
data, which is fundamental to lots of industrial tasks like autonomous driving, defect …

Deep Multi-task image clustering endeavors to leverage deep learning techniques for the
simultaneous processing of multiple clustering tasks. Current multi-task deep image …