3 citations · 7 across the 6 of their papers we have counts for
4 papers · 1 filter
Association and Consolidation: Evolutionary Memory-Enhanced Incremental Multi-View Clustering
Zisen Kong, Bo Zhong, Pengyuan Li +3
Incremental multi-view clustering aims to achieve stable clustering results while addressing the stability-plasticity dilemma (SPD) in view-incremental scenarios. The core challeng…
Revisiting Radar Camera Alignment by Contrastive Learning for 3D Object Detection
Linhua Kong, Dongxia Chang, Lian Liu +3
Recently, 3D object detection algorithms based on radar and camera fusion have shown excellent performance, setting the stage for their application in autonomous driving perception…
Cross-view Graph Contrastive Representation Learning on Partially Aligned Multi-view Data
Yiming Wang, Dongxia Chang, Zhiqiang Fu +2
Multi-view representation learning has developed rapidly over the past decades and has been applied in many fields. However, most previous works assumed that each view is complete…
ACTIVE:Augmentation-Free Graph Contrastive Learning for Partial Multi-View Clustering
Yiming Wang, Dongxia Chang, Zhiqiang Fu +2
In this paper, we propose an augmentation-free graph contrastive learning framework, namely ACTIVE, to solve the problem of partial multi-view clustering. Notably, we suppose that…