Awesome-Deep-Multi-View-Clustering

Collections for state-of-the-art and novel deep neural network-based multi-view clustering approaches (papers & codes). According to the integrity of multi-view data, such methods can be further subdivided into Deep Multi-view Clustering(DMVC) and Deep Incomplete Multi-view Clustering(DIMVC).

We are looking forward for other participants to share their papers and codes. If interested or any question about the listed papers and codes, please contact jinjiaqi@nudt.edu.cn. If you find this repository useful to your research or work, it is really appreciated to star this repository. ✨ If you use our code or the processed datasets in this repository for your research, please cite 1-2 papers in the citation part here. ❤️

Table of Contents

• What's Deep Multi-view Clustering?
• Surveys
• Papers & Codes
  • Deep Multi-view Clustering(DMVC)
  • Deep Incomplete Multi-view Clustering(DIMVC)
• Citation

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What's Deep Multi-view Clustering?

Deep multi-view clustering aims to reveal the potential complementary information of multiple features or modalities through deep neural networks, and finally divide samples into different groups in unsupervised scenarios.

Surveys

Year	Title	Venue	Paper
2025	Deep Multi-view Clustering：A Comprehensive Survey of the Contemporary Techniques	IF
2025	Advanced Unsupervised Learning：A Comprehensive Overview of Multi-view Clustering Techniques	AIR
2024	A Survey and an Empirical Evaluation of Multi-view Clustering Approaches	ACM CS
2024	Self‐Supervised Multi‐View Clustering in Computer Vision: A Survey	IET CV
2024	The Methods for Improving Large-Scale Multi-View Clustering Efficiency: A Survey	AIR
2024	Deep Clustering：A Comprehensive Survey	TNNLS
2024	Breaking Down Multi-view Clustering：A Comprehensive Review of Multi-view Approaches for Complex Data Structures	EAAI
2024	Incomplete Multi-view Learning: Review, Analysis, and Prospects	ASC
2023	A Comprehensive Survey on Multi-view Clustering	TKDE
2022	Representation Learning in Multi-view Clustering: A Literature Review	DSE
2022	Foundations and Recent Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions	Arxiv
2021	Survey on Deep Multi-modal Data Analytics: Collaboration, Rivalry, and Fusion	TOMM
2021	Deep Multi-view Learning Methods: A Review	Neurocom
2018	A Survey of Multi-View Representation Learning	TKDE
2018	Multi-view Clustering: A Survey	BDMA
2018	Multimodal Machine Learning: A Survey and Taxonomy	TPAMI
2018	A Survey on Multi-View Clustering	Arxiv
2017	Multi-view Learning Overview：Recent Progress and New Challenges	IF
2013	A Survey on Multi-view Learning	Arxiv

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Papers & Codes

According to the integrity of multi-view data, the paper is divided into deep multi-view clustering methods and deep incomplete multi-view clustering approaches.

Deep Multi-view Clustering(DMVC)

Year	Title	Abbreviation	Venue	Paper	Code
2026	Balanced Multi-view Clustering	BMvC	TPAMI
2026	Learning Disentangled Representations for Generalized Multi-view Clustering	GMAE	TPAMI
2026	Cross-View Graph Matching for Unsupervised Learning with Unaligned Multi-view Clustering	CGM-CUC	TKDE		-
2026	Pseudo-Label Similarity Graph-Driven Multi-View Contrastive Clustering	PSGVC	TMM		-
2026	Anti-Degradation Lifelong Multi-View Clustering	ALMC	CVPR
2026	Multi-Hierarchical Contrastive Spectral Fusion for Multi-View Clustering	MCSF	CVPR
2026	Reliable Clustering Number Estimation for Contrastive Multi-View Clustering	RCNMC	CVPR		-
2026	Multi-view Clustering with Granularity-aware Pseudo Supervision	GAPS	AAAI		-
2026	Wasserstein-aligned Hyperbolic Multi-view Clustering	WAH-MVC	AAAI
2026	Adaptive Evolutionary Fusion for Multi-View Clustering	AEF-MVC	AAAI
2026	DC-SPAN: A Dual Contrastive Attention Network for Multi-View Clustering	DC-SPAN	AAAI		-
2026	Gated Variational Graph Autoencoders as Experts with Competition and Consensus for Multi-view Clustering	GVGAE-C^2	AAAI		-
2026	Enhanced Federated Deep Multi-View Clustering Under Uncertainty Scenario	EFD-MVC	AAAI		-
2026	Mamba-driven Multi-view Discriminative Clustering via Global-local Cross-view Sequence Modeling	MGLC	AAAI		-
2026	EvoFMVC: Trusted Federated Multi-View Clustering with Evolutionary Fusion	EvoFMVC	AAAI		-
2026	RAC-DMVC: Reliability-Aware Contrastive Deep Multi-View Clustering Under Multi-Source Noise	RAC-DMVC	AAAI
2026	Disentangled Contrastive Multi-view Clustering via Semantic Relevance Invariance	DMVCS	TKDE
2026	Deep Multi-View Clustering With Intra-View Similarity and Cross-View Correlation Learning	MISCC	TMM
2026	Uncertainty-Aware Multi-View Graph Clustering	UMGC-Net	TMM		-
2026	Bridging Optimization and Neural Networks for Efficient Multi-view Clustering	BONE	AAAI
2026	DMCAR: Disentangled Mixture-of-Experts with Context-Aware Routing for Multi-View Clustering	DMCAR	AAAI		-
2026	Hierarchical Cross-View Alignment for Multi-View Clustering via Decoupled Information Distillation	HOARD	AAAI		-
2025	LLM-DAMVC: A Large Language Model Assisted Dynamic Agent for Multi-View Clustering	LLM-DAMVC	NeurIPS		-
2025	SparseMVC: Probing Cross-view Sparsity Variations for Multi-view Clustering	SparseMVC	NeurIPS
2025	Multi-View Graph Clustering via Node-Guided Contrastive Encoding	NGCE	ICML
2025	Automatically Identify and Rectify: Robust Deep Contrastive Multi-view Clustering in Noisy Scenarios	AIRMVC	ICML
2025	PROTOCOL: Partial Optimal Transport-enhanced Contrastive Learning for Imbalanced Multi-view Clustering	PROTOCOL	ICML
2025	Generalized Deep Multi-view Clustering via Causal Learning with Partially Aligned Cross-view Correspondence	CauMVC	ICCV		-
2025	A Hubness Perspective on Representation Learning for Graph-Based Multi-View Clustering	hubREP	CVPR
2025	Deep Fair Multi-View Clustering with Attention KAN	DFMVC-AKAN	CVPR		-
2025	EASEMVC:Efficient Dual Selection Mechanism for Deep Multi-View Clustering	EASEMVC	CVPR		-
2025	Enhanced then Progressive Fusion with View Graph for Multi-View Clustering	EPFMVC	CVPR		-
2025	Medusa: A Multi-Scale High-order Contrastive Dual-Diffusion Approach for Multi-View Clustering	Medusa	CVPR		-
2025	ROLL: Robust Noisy Pseudo-label Learning for Multi-View Clustering with Noisy Correspondence	ROLL	CVPR
2025	Deep Multi-View Contrastive Clustering via Graph Structure Awareness	DMvCGSA	TIP		-
2025	DFL-Net: Disentangled Feature Learning Network for Multi-view Clustering	DFL-Net	TKDE
2025	Pseudo-Label Guided Bidirectional Discriminative Deep Multi-View Subspace Clustering	PBDMSC	TKDE
2025	Multigranularity Information Fused Contrastive Learning With Multiview Clustering	MGCMVC	TNNLS
2025	Multilevel Reliable Guidance for Unpaired Multiview Clustering	MRG-UMC	TNNLS
2025	Learn from Global Rather Than Local: Consistent Context-Aware Representation Learning for Multi-View Graph Clustering	CCARL	IJCAI		-
2025	Graph Embedded Contrastive Learning for Multi-View Clustering	GMVC	IJCAI
2025	MASTER: A Multi-granularity Invariant Structure Clustering Scheme for Multi-view Clustering	MASTER	IJCAI		-
2025	Efficient Multi-view Clustering via Reinforcement Contrastive Learning	EMVC-RCL	IJCAI		-
2025	COPER: Correlation-based Permutations for Multi-View Clustering	COPER	ICLR
2025	Self-supervised Trusted Contrastive Multi-view Clustering with Uncertainty Refined	STCMC-UR	AAAI
2025	Mixture of Experts as Representation Learner for Deep Multi-View Clustering	DMVC-CE	AAAI		-
2025	Structure-Adaptive Multi-View Graph Clustering for Remote Sensing Data	SAMVGC	AAAI		-
2025	Multi-aspect Self-guided Deep Information Bottleneck for Multi-modal Clustering	MSDIB	AAAI
2025	Multi-view Granular-ball Contrastive Clustering	MGBCC	AAAI
2025	Selective Contrastive Learning for Unpaired Multi-View Clustering	scl-UMC	TNNLS		-
2025	EMLFCL: An Efficient Multilevel Fusion Contrastive Learning for Multiview Clustering	EMLFCL	TNNLS		-
2025	Anchor-Sharing and Cluster-Wise Contrastive Network for Multiview Representation Learning	CwCL	TNNLS		-
2025	Multilevel Contrastive Multiview Clustering With Dual Self-Supervised Learning	MCMC	TNNLS		-
2025	Variational Graph Generator for Multiview Graph Clustering	VGMGC	TNNLS
2025	Dynamic Graph Guided Progressive Partial View-Aligned Clustering	DGPPVC	TNNLS		-
2025	Robust Multi-view Clustering via Pseudo Label Guided Universum Learning	PAUSE	ACM MM
2025	CausalMVC: Causal Content-Style Representation Learning for Deep Multi-View Clustering	CausalMVC	ACM MM		-
2025	Neighbor Contrastive Learning with Weakened Consensus Graph for Deep Multi-View Clustering	NCMVC	ACM MM
2025	AEMVC: Mitigate Imbalanced Embedding Space in Multi-view Clustering	AEMVC	ACM MM
2025	Cluster-Aware Contrastive Multi-View Clustering Based on Masked Views	CongeMVC	ACM MM		-
2025	DPFMVC: Dynamic Progressive Fusion for Multi-view Clustering	DPFMVC	ACM MM		-
2025	Deep Discriminative Multi-view Clustering	DDMvC	TCSVT
2025	Graph Variational Multi-view Clustering	GVMVC	TCSVT
2025	A Novel Approach for Effective Partially View-Aligned Clustering with Triple-Consistency	TCLPVC	TCSVT
2025	Learnable Graph Guided Deep Multi-view Representation Learning via Information Bottleneck	LGG-DMRL	TCSVT
2025	Self-supervised Semantic Soft Label Learning Network for Deep Multi-view Clustering	SSLNMVC	TMM
2025	Learning Uniform Latent Representation via Alternating Adversarial Network for Multi-View Clustering	Deep-A2MC	TETCI		-
2025	Multi-layer Multi-level Comprehensive Learning for Deep Multi-view Clustering	3MC	IF
2025	Interpretable Multi-view Clustering	-	PR		-
2025	Deep Multi-view Clustering with Diverse and Discriminative Feature Learning	DDMVC	PR
2024	Adversarially Robust Deep Multi-View Clustering: A Novel Attack and Defense Framework	AR-DMVC-AM	ICML
2024	Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views	FMCSC	NeurIPS
2024	Robust Contrastive Multi-view Clustering against Dual Noisy Correspondence	CANDY	NeurIPS
2024	Evaluate then Cooperate: Shapley-based View Cooperation Enhancement for Multi-view Clustering	SCE-MVC	NeurIPS		-
2024	Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios	MVCAN	CVPR
2024	Rethinking Multi-view Representation Learning via Distilled Disentangling	MRDD	CVPR
2024	Differentiable Information Bottleneck for Deterministic Multi-view Clustering	DIB	CVPR		-
2024	Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders	CMVAE	ICLR		-
2024	Learning Common Semantics via Optimal Transport for Contrastive Multi-view Clustering	CSOT	TIP
2024	Dual Contrast-Driven Deep Multi-View Clustering	DCMVC	TIP
2024	Multiview Deep Subspace Clustering Networks	MvDSCN	TCYB		-
2024	Deep Contrastive Multi-View Subspace Clustering With Representation and Cluster Interactive Learning	DCMVSC	TKDE
2024	Robust Multi-View Clustering with Noisy Correspondence	RMCNC	TKDE
2024	Integrating Vision-Language Semantic Graphs in Multi-View Clustering	IVSGMV	IJCAI		-
2024	Simple Contrastive Multi-View Clustering with Data-Level Fusion	SCM	IJCAI
2024	Dynamic Weighted Graph Fusion for Deep Multi-View Clustering	DFMVC	IJCAI		-
2024	Contrastive and View-Interaction Structure Learning for Multi-view Clustering	SERIES	IJCAI		-
2024	Active Deep Multi-view Clustering	ADMC	IJCAI
2024	Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering	AHGFC	AAAI		-
2024	SURER: Structure-Adaptive Unified Graph Neural Network for Multi-View Clustering	SURER	AAAI
2024	Graph based Consistency Learning for Contrastive Multi-View Clustering	GC-CMVC	ACM MM		-
2024	Heterogeneity-Aware Federated Deep Multi-View Clustering towards Diverse Feature Representations	HFMVC	ACM MM
2024	EMVCC: Enhanced Multi-View Contrastive Clustering for Hyperspectral Images	EMVCC	ACM MM
2024	DFMVC: Deep Fair Multi-view Clustering	DFMVC	ACM MM		-
2024	View Gap Matters: Cross-view Topology and Information Decoupling for Multi-view Clustering	TGM-MVC	ACM MM		-
2024	Learning Dual Enhanced Representation for Contrastive Multi-view Clustering	LUCE-CMC	ACM MM
2024	Contrastive Graph Distribution Alignment for Partially View-Aligned Clustering	CGDA	ACM MM		-
2024	Dual-Optimized Adaptive Graph Reconstruction for Multi-View Graph Clustering	DOAGC	ACM MM		-
2024	Robust Variational Contrastive Learning for Partially View-unaligned Clustering	VITAL	ACM MM
2024	Self-Weighted Contrastive Fusion for Deep Multi-View Clustering	SCMVC	TMM
2024	Subspace-Contrastive Multi-View Clustering	SCMC	TKDD		-
2024	Multi-view contrastive clustering via integrating graph aggregation and confidence enhancement	MAGA	IF
2024	Trustworthy multi-view clustering via alternating generative adversarial representation learning and fusion	AGARL	IF		-
2024	Structural deep multi-view clustering with integrated abstraction and detail	SMVC	NN		-
2024	Progressive Neighbor-masked Contrastive Learning for Fusion-style Deep Multi-View Clustering	PNCL-FDMC	NN		-
2024	Composite Attention Mechanism Network for Deep Contrastive Multi-view Clustering	CAMVC	NN		-
2024	Asymmetric Double-Winged Multi-View Clustering Network for Exploring Diverse and Consistent Information	CodingNet	NN		-
2024	Decomposed deep multi-view subspace clustering with self-labeling supervision	D2MVSC	IS		-
2024	Structure-guided feature and cluster contrastive learning for multi-view clustering	SGFCC	Neurcom		-
2024	Learning consensus representations in multi-latent spaces for multi-view clustering	DMCC	Neurcom		-
2024	MCoCo: Multi-level Consistency Collaborative Multi-view Clustering	MCoCo	ESA		-
2024	Graph-Driven Deep Multi-View Clustering with Self-Paced Learning	GDMVC	KBS
2024	Information Bottleneck Fusion for Deep Multi-view Clustering	IBFDMVC	KBS		-
2024	Separable Consistency and Diversity Feature Learning for Multi-View Clustering	SCDFL	SPL		-
2023	Graph Embedding Contrastive Multi-Modal Representation Learning for Clustering	GECMC	TIP
2023	Neighbor-aware deep multi-view clustering via graph convolutional network	NMvC-GCN	IF
2023	Joint contrastive triple-learning for deep multi-view clustering	JCT	IPM
2023	Auto-attention mechanism for multi-view deep embedding clustering	MDEC	PR		-
2023	Deep multi-view spectral clustering via ensemble	DMCE	PR		-
2023	Unified Representation Learning for Multi-View Clustering by Between/Within View Deep Majorization	deepURL	TETCI
2023	Dropping pathways towards deep multi-view graph subspace clustering networks	DPMGSC	ACM MM		-
2023	Triple-granularity contrastive learning for deep multi-view subspace clustering	TRUST	ACM MM		-
2023	Deep multiview adaptive clustering with semantic invariance	DMAC-SI	TNNLS
2023	Generalized Information-theoretic Multi-view Clustering	IMC	NeurIPS		-
2023	Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration	SEM	NeurIPS
2023	A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective	SUMVC	NeurIPS
2023	Dual Label-Guided Graph Refnement for Multi-View Graph Clustering	DuaLGR	AAAI
2023	Cross-view Topology Based Consistent and Complementary Information for Deep Multi-view Clustering	CTCC	ICCV		-
2023	MHCN: A Hyperbolic Neural Network Model for Multi-view Hierarchical Clustering	MHCN	ICCV		-
2023	Deep Multiview Clustering by Contrasting Cluster Assignments	CVCL	ICCV
2023	DealMVC: Dual Contrastive Calibration for Multi-view Clustering	DealMVC	ACM MM
2023	Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering	SGDMC	AAAI		-
2023	Dual Fusion-Propagation Graph Neural Network for Multi-view Clustering	DFP-GNN	TMM		-
2023	Joint Shared-and-Specific Information for Deep Multi-View Clustering	JSSI	TCSVT		-
2023	On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering	DeepMVC	CVPR
2023	GCFAgg：Global and Cross-view Feature Aggregation for Multi-view Clustering	GCFAgg	CVPR		-
2023	Self-Supervised Information Bottleneck for Deep Multi-View Subspace Clustering	SIB-MSC	TIP		-
2023	Multi-channel Augmented Graph Embedding Convolutional Network for Multi-view Clustering	MAGEC-Net	TNSE		-
2022	Deep Safe Multi-View Clustering：Reducing the Risk of Clustering Performance Degradation Caused by View Increase	DSMVC	CVPR
2022	Multi-level Feature Learning for Contrastive Multi-view Clustering	MFLVC	CVPR
2022	Stationary Diffusion State Neural Estimation for Multiview Clustering	SDSNE	AAAI
2022	Multi-View Subspace Clustering via Structured Multi-Pathway Network	SMpNet	TNNLS
2022	Multiview Subspace Clustering With Multilevel Representations and Adversarial Regularization	MvSC-MRAR	TNNLS		-
2022	Self-Supervised Deep Multiview Spectral Clustering	SDMvSC	TNNLS		-
2022	Contrastive Multi-view Hyperbolic Hierarchical Clustering	CMHHC	IJCAI		-
2022	Multi-view Graph Embedding Clustering Network：Joint Self-supervision and Block Diagonal Representation	MVGC	NN
2022	Efficient Multi‑view Clustering Networks	EMC-Nets	APPL INTELL
2021	Deep Mutual Information Maximin for Cross-Modal Clustering	DMIM	AAAI		-
2021	Uncertainty-Aware Multi-View Representation Learning	DUA-Nets	AAAI
2021	Learning Deep Sparse Regularizers With Applications to Multi-View Clustering and Semi-Supervised Classification	DSRL	TPAMI
2021	Reconsidering Representation Alignment for Multi-view Clustering	SiMVC&CoMVC	CVPR
2021	Deep Multiple Auto-Encoder-Based Multi-view Clustering	MVC_MAE	DSE
2021	Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos	MCN	ICCV
2021	Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering	Multi-VAE	ICCV
2021	Graph Filter-based Multi-view Attributed Graph Clustering	MvAGC	IJCAI
2021	Multi-view Subspace Clustering Networks with Local and Global Graph Information	MSCNGL	Neurocom
2021	Attentive Multi-View Deep Subspace Clustering Net	AMVDSN	Neurocom		-
2021	Multi-view Contrastive Graph Clustering	MCGC	NeurIPS
2021	Self-supervised Discriminative Feature Learning for Deep Multi-view Clustering	SDMVC	TKDE
2021	Multi-view Attributed Graph Clustering	MAGC	TKDE
2021	Deep Multi-view Subspace Clustering with Unified and Discriminative Learning	DMSC-UDL	TMM
2021	Self-supervised Graph Convolutional Network for Multi-view Clustering	SGCMC	TMM
2021	Consistent Multiple Graph Embedding for Multi-View Clustering	CMGEC	TMM
2021	Deep Multiview Collaborative Clustering	DMCC	TNNLS		-
2020	Partially View-aligned Clustering	PVC	NeurIPS
2020	Cross-modal Subspace Clustering via Deep Canonical Correlation Analysis	CMSC-DCCA	AAAI		-
2020	Shared Generative Latent Representation Learning for Multi-View Clustering	DMVCVAE	AAAI
2020	End-to-End Adversarial-Attention Network for Multi-Modal Clustering	EAMC	CVPR
2020	Multi-View Attribute Graph Convolution Networks for Clustering	MAGCN	IJCAI
2020	End-To-End Deep Multimodal Clustering	DMMC	ICME
2020	Deep Embedded Multi-view Clustering with Collaborative Training	DEMVC	IS
2020	Joint Deep Multi-View Learning for Image Clustering	DMJC	TKDE		-
2020	One2Multi Graph Autoencoder for Multi-view Graph Clustering	O2MVC	WWW
2019	AE^2-Nets: Autoencoder in Autoencoder Networks	AE^2-Nets	CVPR
2019	COMIC: Multi-view Clustering Without Parameter Selection	COMIC	ICML
2019	Deep Adversarial Multi-view Clustering Network	DAMC	IJCAI
2019	Multi-view Spectral Clustering Network	MvSCN	IJCAI
2019	Multi-view Deep Subspace Clustering Networks	MvDSCN	TIP
2018	Generalized Latent Multi-View Subspace Clustering	gLMSC	TPAMI
2018	Deep Multimodal Subspace Clustering Networks	DMSC	STSP
2018	Deep Multi-View Clustering via Multiple Embedding	DMVC-ME	CoRR		-

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Deep Incomplete Multi-view Clustering(DIMVC)

Year	Title	Abbreviation	Venue	Paper	Code
2026	Enhancing Multi-View Clustering: A Sufficient Information-Theoretic Approach for Consistency Acquisition and Redundancy Elimination	STMVC	TPAMI
2026	Imbalanced View Contribution Evaluation and Refinement for Deep Incomplete Multi-View Clustering	ICER	CVPR		-
2026	Global-Graph Guided and Local-Graph Weighted Contrastive Learning for Unified Clustering on Incomplete and Noise Multi-View Data	GLGC	CVPR
2026	Structure-Aware Conditional Diffusion Generation for Incomplete Multi-View Clustering	SACDG	TKDE		-
2026	Federated Incomplete Multi-View Clustering With Cross-View Relationship Imputation	FIMCI	TKDE
2026	Geometry-Aware Variational Information Maximization for Deep Incomplete Multi-view Clustering	GAVIM	AAAI
2026	Deep Incomplete Multi-View Clustering via Hierarchical Imputation and Alignment	DIMVC-HIA	AAAI
2026	Dynamic Deep Graph Learning for Incomplete Multi-View Clustering with Masked Graph Reconstruction Loss	DGIMVCM	AAAI
2026	Adversarial Fair Incomplete Multi-View Clustering	AFIMVC	AAAI		-
2025	Incomplete Multi-view Clustering via Hierarchical Semantic Alignment and Cooperative Completion	HSACC	NeurIPS
2025	Learning from Disjoint Views: A Contrastive Prototype Matching Network for Fully Incomplete Multi-View Clustering	CPMN	NeurIPS		-
2025	An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective	ESFMC	ICML
2025	Federated Incomplete Multi-view Clustering with Globally Fused Graph Guidance	FIMCFG	ICML
2025	A Unified Framework to BRIDGE Complete and Incomplete Deep Multi-View Clustering under Non-IID Missing Patterns	BRIDGE	ICCV
2025	Deep Incomplete Multi-view Clustering with Distribution Dual-Consistency Recovery Guidance	BURG	ICCV
2025	Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs	MVP	ICLR
2025	Imputation-free and Alignment-free: Incomplete Multi-view Clustering Driven by Consensus Semantic Learning	FreeCSL	CVPR
2025	Robust Graph Contrastive Learning for Incomplete Multi-view Clustering	RGCL	IJCAI
2025	LRGR: Self-Supervised Incomplete Multi-View Clustering via Local Refinement and Global Realignment	LRGR	IJCAI		-
2025	Fair Incomplete Multi-View Clustering via Distribution Alignment	FIMVC-DA	IJCAI		-
2025	Dual Robust Unbiased Multi-View Clustering for Incomplete and Unpaired Information	DRUMVC	IJCAI		-
2025	Imputation-free Incomplete Multi-view Clustering via Knowledge Distillation	I2MVC	IJCAI		-
2025	Incomplete and Unpaired Multi-View Graph Clustering with Cross-View Feature Fusion	MGCCFF	AAAI
2025	Incomplete Multi-view Clustering via Diffusion Contrastive Generation	DCG	AAAI
2025	Global Graph Propagation with Hierarchical Information Transfer for Incomplete Contrastive Multi-view Clustering	GHICMC	AAAI
2025	Deep Variational Incomplete Multi-View Clustering with Information-Theoretic Guidance	DVIMC-ITG	ACM MM		-
2025	DUIMC: Deep Unbalanced Incomplete Multi-View Clustering via Graph Constrained Imputation and Contrastive Learning	DUIMC	ACM MM		-
2025	Energy-based Deep Incomplete Multi-View Clustering	Energy-DIMC	ACM MM
2025	Dual-level Distribution Alignment for Deep Incomplete Multi-view Clustering	DDAIMVC	ACM MM		-
2025	Selective Cross-view Topology for Deep Incomplete Multi-view Clustering	SCVT	TIP
2025	Prototype Matching Learning for Incomplete Multi-view Clustering	PMIMC	TIP
2025	Incomplete Multi-View Clustering via Multi-Level Contrastive Learning	IMC-MCL	TKDE
2025	Neighbor-Based Completion for Addressing Incomplete Multiview Clustering	NBIMVC	TNNLS
2025	Incomplete Multi-View Clustering via Mutual Information	IMCMI	TMM		-
2025	Deep Incomplete Multi-View Clustering via Dynamic Imputation and Triple Alignment With Dual Optimization	DITA-IMVC	TCSVT
2025	Mask-informed Deep Contrastive Incomplete Multi-view Clustering	Mask-IMvC	TCSVT
2025	Incomplete Multi-view Clustering Based on Information Fusion with Self-supervised Learning	IMCFL	IF		-
2025	Deep Incomplete Multi-view Clustering via Multi-level Imputation and Contrastive Alignment	MICA	PR		-
2024	Explicit View-Labels Matter: A Multifacet Complementarity Study of Multi-View Clustering	MCMVC	TPAMI		-
2024	Diffusion-based Missing-view Generation With the Application on Incomplete Multi-view Clustering	DMVG	ICML
2024	Deep Variational Incomplete Multi-View Clustering: Exploring Shared Clustering Structures	DVIMC	AAAI
2024	Partial Multi-View Clustering via Self-Supervised Network	PVC-SCN	AAAI
2024	Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding	ICMVC	AAAI
2024	Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering	AGDIMC	AAAI		-
2024	Decoupled Contrastive Multi-view Clustering with High-order Random Walks	DIVIDE	AAAI
2024	Robust Prototype Completion for Incomplete Multi-view Clustering	RPCIC	ACM MM
2024	URRL-IMVC: Unified and Robust Representation Learning for Incomplete Multi-View Clustering	URRL-IMVC	KDD		-
2024	Subgraph Propagation and Contrastive Calibration for Incomplete Multiview Data Clustering	SPCC	TNNLS		-
2024	Deep Incomplete Multiview Clustering via Local and Global Pseudo-Label Propagation	PLP-IMVC	TNNLS		-
2024	Robust Multi-Graph Contrastive Network for Incomplete Multi-View Clustering	RMGC	TMM		-
2024	A novel Federated Multi-view Clustering Method for Unaligned and Incomplete Data Fusion	FUCIF	IF
2024	Contrastive and Adversarial Regularized Multi-level Representation Learning for Incomplete Multi-view Clustering	MRL_CAL	NN
2024	View-interactive Attention Information Alignment-guided Fusion for Incomplete Multi-view Clustering	VAIAF	ESA		-
2024	Graph-Guided Imputation-Free Incomplete Multi-View Clustering	GIMVC	ESA
2024	Deep Incomplete Multi-View Clustering via Attention-Based Direct Contrastive Learning	ADCL	ESA		-
2024	Incomplete Multi-View Clustering Via Inference and Evaluation	IMVC-IE	ICASSP
2023	UNTIE: Clustering Analysis with Disentanglement in Multi-view Information Fusion	UNTIE	IF		-
2023	Federated Deep Multi-View Clustering with Global Self-Supervision	FedDMVC	ACM MM		-
2023	Information Recovery-driven Deep Incomplete Multiview Clustering Network	RecFormer	TNNLS
2023	Realize Generative Yet Complete Latent Representation for Incomplete Multi-View Learning	CMVAE	TPAMI		-
2023	Semantic Invariant Multi-View Clustering With Fully Incomplete Information	SMILE	TPAMI
2023	Deep Incomplete Multi-view Clustering with Cross-view Partial Sample and Prototype Alignment	CPSPAN	CVPR
2023	Adaptive Feature Projection with Distribution Alignment for Deep Incomplete Multi-view Clustering	APADC	TIP
2023	Incomplete Multi-view Clustering via Prototype-based Imputation	ProImp	IJCAI
2023	Consistent Graph Embedding Network with Optimal Transport for Incomplete Multi-view Clustering	CGEN-OT	IS		-
2023	CCR-Net: Consistent Contrastive Representation Network for Multi-view Clustering	CCR-Net	IS
2023	Incomplete Multi-view Clustering Network via Nonlinear Manifold Embedding and Probability-Induced Loss	IMCNet-MP	NN		-
2022	Robust Multi-view Clustering with Incomplete Information	SURE	TPAMI
2022	Dual Contrastive Prediction for Incomplete Multi-view Representation Learning	DCP	TPAMI
2022	Deep Safe Incomplete Multi-view Clustering: Theorem and Algorithm	DSIMVC	ICML
2022	Deep Incomplete Multi-view Clustering via Mining Cluster Complementarity	DIMVC	AAAI
2022	Robust Diversified Graph Contrastive Network for Incomplete Multi-view Clustering	RDGC	ACM MM
2022	Incomplete Multi-view Clustering via Cross-view Relation Transfer	CRTC	TCSVT
2022	Graph Contrastive Partial Multi-view Clustering	AGCL	TMM
2021	COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction	COMPLETER	CVPR
2021	iCmSC: Incomplete Cross-modal Subspace Clustering	iCmSC	TIP
2021	Generative Partial Multi-View Clustering With Adaptive Fusion and Cycle Consistency	GP-MVC	TIP
2021	Clustering-Induced Adaptive Structure Enhancing Network for Incomplete Multi-View Data	CASEN	IJCAI		-
2021	Structural Deep Incomplete Multi-view Clustering Network	SDIMC-net	CIKM		-
2020	Deep Partial Multi-View Learning	DPML	TPAMI
2020	CDIMC-net：Cognitive Deep Incomplete Multi-view Clustering Network(	CDIMC-net	IJCAI
2020	DIMC-net：Deep Incomplete Multi-view Clustering Network	DIMC-net	ACM MM		-
2020	Deep Incomplete Multi-View Multiple Clusterings	DiMVMC	ICDM
2019	CPM-Nets: Cross Partial Multi-View Networks	CPM-Nets	NeurIPS
2019	Adversarial Incomplete Multi-view Clustering	AIMC	IJCAI		-
2018	Partial Multi-View Clustering via Consistent GAN	PVC-GAN	ICDM

---

Citation

@inproceedings{jin2025deep,
  title={Deep incomplete multi-view clustering with distribution dual-consistency recovery guidance},
  author={Jin, Jiaqi and Wang, Siwei and Dong, Zhibin and Yang, Xihong and Liu, Xinwang and Zhu, En and He, Kunlun},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={1016--1026},
  year={2025}
}

@inproceedings{jin2023deep,
  title={Deep Incomplete Multi-view Clustering with Cross-view Partial Sample and Prototype Alignment},
  author={Jin, Jiaqi and Wang, Siwei and Dong, Zhibin and Liu, Xinwang and Zhu, En},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={11600--11609},
  year={2023}
}

@inproceedings{wangevaluate,
  title={Evaluate then Cooperate: Shapley-based View Cooperation Enhancement for Multi-view Clustering},
  author={Wang, Fangdi and Jin, Jiaqi and Hu, Jingtao and Liu, Suyuan and Yang, Xihong and Wang, Siwei and Liu, Xinwang and Zhu, En},
  booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems}
}

@article{yang2025automatically,
  title={Automatically identify and rectify: Robust deep contrastive multi-view clustering in noisy scenarios},
  author={Yang, Xihong and Wang, Siwei and Wang, Fangdi and Jin, Jiaqi and Liu, Suyuan and Liu, Yue and Zhu, En and Liu, Xinwang and Jin, Yueming},
  journal={arXiv preprint arXiv:2505.21387},
  year={2025}
}

@inproceedings{yang2025generalized,
  title={Generalized Deep Multi-view Clustering via Causal Learning with Partially Aligned Cross-view Correspondence},
  author={Yang, Xihong and Wang, Siwei and Jin, Jiaqi and Wang, Fangdi and Liu, Tianrui and Jin, Yueming and Liu, Xinwang and Zhu, En and He, Kunlun},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={1990--1999},
  year={2025}
}

@inproceedings{xiao2026dmcar,
  title={DMCAR: Disentangled Mixture-of-Experts with Context-Aware Routing for Multi-View Clustering},
  author={Xiao, Baili and Liang, Ke and Jin, Jiaqi and Wang, Jun and Xu, Yinbo and Wang, Siwei and Zhu, En},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={40},
  number={32},
  pages={27055--27063},
  year={2026}
}

@inproceedings{zhou2026hierarchical,
  title={Hierarchical Cross-View Alignment for Multi-View Clustering via Decoupled Information Distillation},
  author={Zhou, Taichun and Wang, Siwei and Dong, Zhibin and Jin, Jiaqi and Liang, Ke and Xiao, Baili and Li, Miaomiao and Liu, Xinwang and Zhu, En},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={40},
  number={34},
  pages={29000--29008},
  year={2026}
}

@article{wang2022align,
  title={Align then fusion: Generalized large-scale multi-view clustering with anchor matching correspondences},
  author={Wang, Siwei and Liu, Xinwang and Liu, Suyuan and Jin, Jiaqi and Tu, Wenxuan and Zhu, Xinzhong and Zhu, En},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={5882--5895},
  year={2022}
}

@inproceedings{dai2025imputation,
  title={Imputation-free and alignment-free: Incomplete multi-view clustering driven by consensus semantic learning},
  author={Dai, Yuzhuo and Jin, Jiaqi and Dong, Zhibin and Wang, Siwei and Liu, Xinwang and Zhu, En and Yang, Xihong and Gan, Xinbiao and Feng, Yu},
  booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference},
  pages={5071--5081},
  year={2025}
}

@inproceedings{dong2025enhanced,
  title={Enhanced then progressive fusion with view graph for multi-view clustering},
  author={Dong, Zhibin and Liu, Meng and Wang, Siwei and Liang, Ke and Zhang, Yi and Liu, Suyuan and Jin, Jiaqi and Liu, Xinwang and Zhu, En},
  booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference},
  pages={15518--15527},
  year={2025}
}

@article{dong2025selective,
  title={Selective cross-view topology for deep incomplete multi-view clustering},
  author={Dong, Zhibin and Hu, Dayu and Jin, Jiaqi and Wang, Siwei and Liu, Xinwang and Zhu, En},
  journal={IEEE Transactions on Image Processing},
  year={2025},
  publisher={IEEE}
}

@inproceedings{dong2023cross,
  title={Cross-view topology based consistent and complementary information for deep multi-view clustering},
  author={Dong, Zhibin and Wang, Siwei and Jin, Jiaqi and Liu, Xinwang and Zhu, En},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={19440--19451},
  year={2023}
}

@inproceedings{yang2023dealmvc,
  title={Dealmvc: Dual contrastive calibration for multi-view clustering},
  author={Yang, Xihong and Jiaqi, Jin and Wang, Siwei and Liang, Ke and Liu, Yue and Wen, Yi and Liu, Suyuan and Zhou, Sihang and Liu, Xinwang and Zhu, En},
  booktitle={Proceedings of the 31st ACM International Conference on Multimedia},
  pages={337--346},
  year={2023}
}

@inproceedings{wang2024view,
  title={View Gap Matters: Cross-view Topology and Information Decoupling for Multi-view Clustering},
  author={Wang, Fangdi and Jin, Jiaqi and Dong, Zhibin and Yang, Xihong and Feng, Yu and Liu, Xinwang and Zhu, Xinzhong and Wang, Siwei and Liu, Tianrui and Zhu, En},
  booktitle={Proceedings of the 32nd ACM International Conference on Multimedia},
  pages={8431--8440},
  year={2024}
}

@article{dong2024subgraph,
  title={Subgraph Propagation and Contrastive Calibration for Incomplete Multiview Data Clustering},
  author={Dong, Zhibin and Jin, Jiaqi and Xiao, Yuyang and Xiao, Bin and Wang, Siwei and Liu, Xinwang and Zhu, En},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2024},
  publisher={IEEE}
}

@article{dong2023iterative,
  title={Iterative deep structural graph contrast clustering for multiview raw data},
  author={Dong, Zhibin and Jin, Jiaqi and Xiao, Yuyang and Wang, Siwei and Zhu, Xinzhong and Liu, Xinwang and Zhu, En},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2023},
  publisher={IEEE}
}