10 citations · 18 across the 2 of their papers we have counts for
3 papers
cs.CV2024★ 10 cited
Masked Two-channel Decoupling Framework for Incomplete Multi-view Weak Multi-label Learning
Chengliang Liu, Jie Wen, Yabo Liu +4
Multi-view learning has become a popular research topic in recent years, but research on the cross-application of classic multi-label classification and multi-view learning is stil…
cs.CV2023
Information Recovery-Driven Deep Incomplete Multiview Clustering Network
Chengliang Liu, Jie Wen, Zhihao Wu +3
Incomplete multi-view clustering is a hot and emerging topic. It is well known that unavoidable data incompleteness greatly weakens the effective information of multi-view data. To…
cs.CV2023★ 8 cited
DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification
Chengliang Liu, Jie Wen, Xiaoling Luo +3
In recent years, multi-view multi-label learning has aroused extensive research enthusiasm. However, multi-view multi-label data in the real world is commonly incomplete due to the…