Multi-view Subspace Clustering

16 papers with code • 2 benchmarks • 1 datasets

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Most implemented papers

High-order Correlation Preserved Incomplete Multi-view Subspace Clustering

guanyuezhen/HCP-IMSC IEEE Transactions on Image Processing 2022

Specifically, multiple affinity matrices constructed from the incomplete multi-view data are treated as a thirdorder low rank tensor with a tensor factorization regularization which preserves the high-order view correlation and sample correlation.

Multi-view Low-rank Sparse Subspace Clustering

mbrbic/Multi-view-LRSSC 29 Aug 2017

Most existing approaches address multi-view subspace clustering problem by constructing the affinity matrix on each view separately and afterwards propose how to extend spectral clustering algorithm to handle multi-view data.

Multi-view Deep Subspace Clustering Networks

yxjdarren/mvdscn 6 Aug 2019

Dnet learns view-specific self-representation matrices, whereas Unet learns a common self-representation matrix for all views.

Large-scale Multi-view Subspace Clustering in Linear Time

sckangz/LMVSC 21 Nov 2019

A plethora of multi-view subspace clustering (MVSC) methods have been proposed over the past few years.

Deep Multimodal Subspace Clustering Networks

mahdiabavisani/Deep-multimodal-subspace-clustering-networks 17 Apr 2018

In addition to various spatial fusion-based methods, an affinity fusion-based network is also proposed in which the self-expressive layer corresponding to different modalities is enforced to be the same.

Feature Concatenation Multi-view Subspace Clustering

ZQH92/FCMSC 30 Jan 2019

To this end, this paper proposes a novel multi-view subspace clustering approach dubbed Feature Concatenation Multi-view Subspace Clustering (FCMSC), which boosts the clustering performance by exploring the consensus information of multi-view data.

Constrained Bilinear Factorization Multi-view Subspace Clustering

ZQH92/CBF-MSC 19 Jun 2019

Multi-view clustering is an important and fundamental problem.

Adaptive multi-view subspace clustering for high-dimensional data,

x-d-wang/x-d-wang.github.io Pattern Recognition Letters 2020

With the rapid development of multimedia technologies, we frequently confront with high-dimensional data and multi-view data, which usually contain redundant features and distinct types of features.

Multi-view Subspace Clustering Networks with Local and Global Graph Information

ZQH92/MSCNLG 19 Oct 2020

Furthermore, underlying graph information of multi-view data is always ignored in most existing multi-view subspace clustering methods.

Unbalanced Incomplete Multi-view Clustering via the Scheme of View Evolution: Weak Views are Meat; Strong Views do Eat

ZeusDavide/TETCI_UIMC 20 Nov 2020

However, different views often have distinct incompleteness, i. e., unbalanced incompleteness, which results in strong views (low-incompleteness views) and weak views (high-incompleteness views).