5 citations · 7 across the 4 of their papers we have counts for
5 papers
Learning Disentangled Representations for Generalized Multi-view Clustering
Xin Zou, Ruimeng Liu, Chang Tang +4
Multi-View Clustering (MVC) has gained significant attention for its ability to leverage complementary information across diverse views. However, existing deep MVC methods often st…
Mask-informed Deep Contrastive Incomplete Multi-view Clustering
Zhenglai Li, Yuqi Shi, Xiao He +1
Multi-view clustering (MvC) utilizes information from multiple views to uncover the underlying structures of data. Despite significant advancements in MvC, mitigating the impact of…
Balanced Multi-view Clustering
Zhenglai Li, Jun Wang, Chang Tang +3
Multi-view clustering (MvC) aims to integrate information from different views to enhance the capability of the model in capturing the underlying data structures. The widely used j…
MS-Former: Memory-Supported Transformer for Weakly Supervised Change Detection with Patch-Level Annotations
Zhenglai Li, Chang Tang, Xinwang Liu +3
Fully supervised change detection methods have achieved significant advancements in performance, yet they depend severely on acquiring costly pixel-level labels. Considering that t…
Hard Region Aware Network for Remote Sensing Change Detection
Zhenglai Li, Chang Tang, Xinwang Liu +4
Change detection (CD) is essential for various real-world applications, such as urban management and disaster assessment. Numerous CD methods have been proposed, and considerable r…