Article

Multi-view Subspace Clustering

Authors:

Hongchang Gao,

Feiping Nie,

Xuelong Li,

Heng HuangAuthors Info & Claims

ICCV '15: Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV)

Pages 4238 - 4246

https://doi.org/10.1109/ICCV.2015.482

Published: 07 December 2015 Publication History

Abstract

For many computer vision applications, the data sets distribute on certain low-dimensional subspaces. Subspace clustering is to find such underlying subspaces and cluster the data points correctly. In this paper, we propose a novel multi-view subspace clustering method. The proposed method performs clustering on the subspace representation of each view simultaneously. Meanwhile, we propose to use a common cluster structure to guarantee the consistence among different views. In addition, an efficient algorithm is proposed to solve the problem. Experiments on four benchmark data sets have been performed to validate our proposed method. The promising results demonstrate the effectiveness of our method.

Cited By

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Wang ZLiu ZHu DJia TLarson K(2024)Nonconvex multiview subspace clustering framework with efficient method designs and theoretical analysisProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/571(5162-5170)Online publication date: 3-Aug-2024
https://dl.acm.org/doi/10.24963/ijcai.2024/571
Lyu GKang WWang HLi ZYang ZFeng SLarson K(2024)Common-individual semantic fusion for multi-view multi-label learningProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/521(4715-4723)Online publication date: 3-Aug-2024
https://dl.acm.org/doi/10.24963/ijcai.2024/521
Fu LHuang SZhang LYang JZheng ZZhang CChen C(2024)Subspace-Contrastive Multi-View ClusteringACM Transactions on Knowledge Discovery from Data10.1145/367483918:9(1-35)Online publication date: 28-Jun-2024
https://dl.acm.org/doi/10.1145/3674839
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Multi-view Subspace Clustering
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning

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ICCV '15: Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV)

December 2015

4730 pages

ISBN:9781467383912

Publisher

IEEE Computer Society

United States

Publication History

Published: 07 December 2015

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Wang ZLiu ZHu DJia TLarson K(2024)Nonconvex multiview subspace clustering framework with efficient method designs and theoretical analysisProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/571(5162-5170)Online publication date: 3-Aug-2024
https://dl.acm.org/doi/10.24963/ijcai.2024/571
Lyu GKang WWang HLi ZYang ZFeng SLarson K(2024)Common-individual semantic fusion for multi-view multi-label learningProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/521(4715-4723)Online publication date: 3-Aug-2024
https://dl.acm.org/doi/10.24963/ijcai.2024/521
Fu LHuang SZhang LYang JZheng ZZhang CChen C(2024)Subspace-Contrastive Multi-View ClusteringACM Transactions on Knowledge Discovery from Data10.1145/367483918:9(1-35)Online publication date: 28-Jun-2024
https://dl.acm.org/doi/10.1145/3674839
Li QLuo TJiang MLiao JJiang ZCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Deep Incomplete Multi-View Network Semi-Supervised Multi-Label Learning with Unbiased LossProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681414(9048-9056)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681414
Qu QWan XLiang WLiu JFeng YXu HLiu XZhu ECai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)A Lightweight Anchor-Based Incremental Framework for Multi-view ClusteringProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680837(8652-8661)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3680837
Du YLu GJi G(2024)Robust Least Squares Regression for Subspace Clustering: A Multi-View Clustering PerspectiveIEEE Transactions on Image Processing10.1109/TIP.2023.332756433(216-227)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIP.2023.3327564
Liu JCao FJing XLiang J(2024)Deep multi-view graph clustering network with weighting mechanism and collaborative trainingExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121298236:COnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121298
Pan BLi CChe H(2024)Error-robust multi-view subspace clustering with nonconvex low-rank tensor approximation and hyper-Laplacian graph embeddingEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108274133:PCOnline publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1016/j.engappai.2024.108274
Xu KTang KSu Z(2024)Multi-view deep subspace clustering via level-by-level guided multi-level features learningApplied Intelligence10.1007/s10489-024-05807-154:21(11083-11102)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1007/s10489-024-05807-1
Chen M(2023)Multi-view Subspace Clustering Based on Feature Integration and Spectral Inner Product FusionProceedings of the 2023 6th International Conference on Algorithms, Computing and Artificial Intelligence10.1145/3639631.3639685(327-332)Online publication date: 22-Dec-2023
https://dl.acm.org/doi/10.1145/3639631.3639685
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Partial Multi-view Subspace Clustering

Multi-geometric Sparse Subspace Clustering

Multi-view clustering via pairwise sparse subspace representation

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