Incomplete multi-view clustering

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

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Datasets archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

17 shown of 17 papers with code (44 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• High-order Correlation Preserved Incomplete Multi-view Subspace Clustering
  21 Feb 2022 3 repositories listed
  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…
• Information Recovery-Driven Deep Incomplete Multiview Clustering Network
  2 Apr 2023 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Concretely, a two-stage autoencoder network with the self-attention structure is built to synchronously extract high-level semantic representations of multiple views and recover the missing data.
• COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction
  22 Mar 2021 2 repositories listed
  In this paper, we study two challenging problems in incomplete multi-view clustering analysis, namely, i) how to learn an informative and consistent representation among different views without the help of labels and…
• Mask-informed Deep Contrastive Incomplete Multi-view Clustering
  4 Feb 2025 1 repository listed
  Multi-view clustering (MvC) utilizes information from multiple views to uncover the underlying structures of data.
• Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding
  14 Dec 2023 1 repository listed Syntology ran 10 of 16 samples · 6 unverified · 16 pointer-only (licence)
  In this work, we proposed a novel Incomplete Contrastive Multi-View Clustering method with high-confidence guiding (ICMVC).
• Joint Projection Learning and Tensor Decomposition Based Incomplete Multi-view Clustering
  6 Oct 2023 1 repository listed
  We further consider the graph noise of projected data caused by missing samples and use a tensor-decomposition based graph filter for robust clustering.
• Scalable Incomplete Multi-View Clustering with Structure Alignment
  31 Aug 2023 1 repository listed
  Although several anchor-based IMVC methods have been proposed to process the large-scale incomplete data, they still suffer from the following drawbacks: i) Most existing approaches neglect the inter-view discrepancy…
• Incomplete Multi-view Clustering via Prototype-based Imputation
  26 Jan 2023 1 repository listed Syntology ran 1 of 10 samples · 9 unverified
  Thanks to our dual-stream model, both cluster- and view-specific information could be captured, and thus the instance commonality and view versatility could be preserved to facilitate IMvC.
• Highly Confident Local Structure Based Consensus Graph Learning for Incomplete Multi-View Clustering
  1 Jan 2023 1 repository listed
  Graph-based multi-view clustering has attracted extensive attention because of the powerful clustering-structure representation ability and noise robustness.
• Robust Diversified Graph Contrastive Network for Incomplete Multi-view Clustering
  10 Oct 2022 1 repository listed
  To address these issues, we propose a Robust Diversified Graph Contrastive Network (RDGC) for incomplete multi-view clustering, which integrates multi-view representation learning and diversified graph contrastive…
• A Survey on Incomplete Multi-view Clustering
  17 Aug 2022 1 repository listed
  However, in practical applications, such as disease diagnosis, multimedia analysis, and recommendation system, it is common to observe that not all views of samples are available in many cases, which leads to the…
• Localized Sparse Incomplete Multi-view Clustering
  5 Aug 2022 1 repository listed
  Moreover, a novel local graph embedding term is introduced to learn the structured consensus representation.
• Highly-Efficient Incomplete Large-Scale Multi-View Clustering With Consensus Bipartite Graph
  1 Jan 2022 1 repository listed
  Multi-view clustering has received increasing attention due to its effectiveness in fusing complementary information without manual annotations.
• Tensor-Based Multi-View Block-Diagonal Structure Diffusion for Clustering Incomplete Multi-View Data
  9 Jun 2021 1 repository listed
  In this paper, we propose a novel incomplete multi-view clustering method, in which a tensor nuclear norm regularizer elegantly diffuses the information of multi-view block-diagonal structure across different views.
• V3H: View Variation and View Heredity for Incomplete Multi-view Clustering
  23 Nov 2020 1 repository listed
  Inspired by the variation and the heredity in genetics, V3H first decomposes each subspace into a variation matrix for the corresponding view and a heredity matrix for all the views to represent the unique information…
• Unbalanced Incomplete Multi-view Clustering via the Scheme of View Evolution: Weak Views are Meat; Strong Views do Eat
  20 Nov 2020 1 repository listed
  However, different views often have distinct incompleteness, i.
• ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view Clustering
  20 Nov 2020 1 repository listed
  In these scenarios, original image data often contain missing instances and noises, which is ignored by most multi-view clustering methods.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.