SOTAVerified

Image Clustering

Models that partition the dataset into semantically meaningful clusters without having access to the ground truth labels.

Image credit: ImageNet clustering results of SCAN: Learning to Classify Images without Labels (ECCV 2020)

Papers

Showing 51–100 of 236 papers

TitleStatusHype
Exploring the Limits of Deep Image Clustering using Pretrained ModelsCode1
Contrastive Hierarchical ClusteringCode1
A Provable Splitting Approach for Symmetric Nonnegative Matrix Factorization—0
Local Connectivity-Based Density Estimation for Face ClusteringCode1
C3: Cross-instance guided Contrastive ClusteringCode1
Twin Contrastive Learning for Online ClusteringCode1
Deep Fair Clustering via Maximizing and Minimizing Mutual Information: Theory, Algorithm and MetricCode0
Improving Image Clustering through Sample Ranking and Its Application to remote--sensing imagesCode0
Self-supervised Image Clustering from Multiple Incomplete Views via Constrastive Complementary Generation—0
Contrastive learning for unsupervised medical image clustering and reconstruction—0
Clustering Without Knowing How To: Application and EvaluationCode0
Efficient Deep Clustering of Human Activities and How to Improve EvaluationCode0
Joint Debiased Representation and Image Clustering Learning with Self-Supervision—0
Semantic-Enhanced Image Clustering—0
Deep Image Clustering with Contrastive Learning and Multi-scale Graph Convolutional NetworksCode1
Vision Transformer for Contrastive ClusteringCode1
Deep embedded clustering algorithm for clustering PACS repositories—0
Attention-based Dynamic Subspace Learners for Medical Image Analysis—0
DeepCluE: Enhanced Image Clustering via Multi-layer Ensembles in Deep Neural Networks—0
HIRL: A General Framework for Hierarchical Image Representation LearningCode1
Image Trinarization Using a Partial Differential Equations: A Novel Approach to Automatic Sperm Image Analysis—0
Fully Automated Binary Pattern Extraction For Finger Vein Identification using Double Optimization Stages-Based Unsupervised Learning Approach—0
There’s a Time and Place for Reasoning Beyond the ImageCode1
Unsupervised detection of ash dieback disease (Hymenoscyphus fraxineus) using diffusion-based hyperspectral image clustering—0
Time Series Clustering for Grouping Products Based on Price and Sales Patterns—0
Unsupervised Diffusion and Volume Maximization-Based Clustering of Hyperspectral ImagesCode0
There is a Time and Place for Reasoning Beyond the ImageCode1
Subspace Co-clustering with Two-Way Graph ConvolutionCode0
Spectral image clustering on dual-energy CT scans using functional regression mixturesCode0
Optimal Estimation and Computational Limit of Low-rank Gaussian Mixtures—0
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly TypesCode1
Use Image Clustering to Facilitate Technology Assisted Review—0
Out-of-Distribution Detection Without Class Labels—0
Sparse Subspace Clustering Friendly Deep Dictionary Learning for Hyperspectral Image Classification—0
Learning Representation for Clustering via Prototype Scattering and Positive SamplingCode1
There’s a Time and Place for Reasoning Beyond the Image—0
Large-Scale Hyperspectral Image Clustering Using Contrastive LearningCode0
Spectral unmixing of Raman microscopic images of single human cells using Independent Component Analysis—0
One Stage Autoencoders for Multi-Domain Learning—0
Language-Guided Image Clustering—0
Cluster Analysis with Deep Embeddings and Contrastive Learning—0
Joint Debiased Representation Learning and Imbalanced Data Clustering—0
MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous DrivingCode1
Deep Relational Metric LearningCode1
Clustering by Maximizing Mutual Information Across Views—0
A Simple Approach to Automated Spectral ClusteringCode0
Selective Pseudo-label ClusteringCode1
Deep Visual Attention-Based Transfer Clustering—0
Neural Mixture Models with Expectation-Maximization for End-to-end Deep Clustering—0
Learning Hierarchical Graph Neural Networks for Image ClusteringCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TURTLE (CLIP + DINOv2)Accuracy1—Unverified
2PRCut (CLIP)Accuracy0.98—Unverified
3PRO-DSCAccuracy0.97—Unverified
4TEMI CLIP ViT-L (openai)Accuracy0.97—Unverified
5DPACAccuracy0.93—Unverified
6SPICE-BPAAccuracy0.93—Unverified
7SeCuAccuracy0.93—Unverified
8TACAccuracy0.92—Unverified
9SPICE*Accuracy0.92—Unverified
10DCN+BRBAccuracy0.91—Unverified
#ModelMetricClaimedVerifiedStatus
1TURTLE (CLIP + DINOv2)Accuracy0.9—Unverified
2PRCut (DinoV2)Accuracy0.79—Unverified
3PRO-DSCAccuracy0.77—Unverified
4TEMI CLIP ViT-L (openai)Accuracy0.74—Unverified
5TEMI DINO ViT-BAccuracy0.67—Unverified
6ITAEAccuracy0.65—Unverified
7SPICE*Accuracy0.58—Unverified
8DPACAccuracy0.56—Unverified
9HUMEAccuracy0.56—Unverified
10SPICE-BPAAccuracy0.55—Unverified
#ModelMetricClaimedVerifiedStatus
1TURTLE (CLIP + DINOv2)Accuracy1—Unverified
2TEMI DINO ViT-BAccuracy0.99—Unverified
3TACAccuracy0.98—Unverified
4SPICE-BPAAccuracy0.94—Unverified
5DPACAccuracy0.93—Unverified
6SPICE*Accuracy0.93—Unverified
7HUMEAccuracy0.91—Unverified
8TCLAccuracy0.87—Unverified
9RUCAccuracy0.87—Unverified
10IMC-SwAV (Best)Accuracy0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1MAE-CT (best)Accuracy0.94—Unverified
2MAE-CT (mean)Accuracy0.87—Unverified
3PRO-DSCAccuracy0.84—Unverified
4ProPos*Accuracy0.78—Unverified
5ProPosAccuracy0.75—Unverified
6DPACAccuracy0.73—Unverified
7ConCURLAccuracy0.7—Unverified
8SPICEAccuracy0.68—Unverified
9TCLAccuracy0.64—Unverified
10IDFDAccuracy0.59—Unverified
#ModelMetricClaimedVerifiedStatus
1TACNMI0.99—Unverified
2SPICENMI0.93—Unverified
3DPACNMI0.93—Unverified
4ProPos*NMI0.91—Unverified
5ConCURLNMI0.91—Unverified
6CoHiClustNMI0.91—Unverified
7C3NMI0.91—Unverified
8IDFDNMI0.9—Unverified
9ProPosNMI0.9—Unverified
10TCLNMI0.88—Unverified
#ModelMetricClaimedVerifiedStatus
1SPCNMI0.98—Unverified
2ADECNMI0.97—Unverified
3N2D (UMAP)NMI0.96—Unverified
4DynAENMI0.96—Unverified
5DDC-DANMI0.96—Unverified
6DENNMI0.96—Unverified
7DTI-ClusteringNMI0.94—Unverified
8EnSCNMI0.94—Unverified
9ClusterGANNMI0.94—Unverified
10DBCNMI0.94—Unverified
#ModelMetricClaimedVerifiedStatus
1SPCNMI0.95—Unverified
2DynAENMI0.95—Unverified
3DENNMI0.94—Unverified
4DDC-DANMI0.94—Unverified
5SR-K-meansNMI0.94—Unverified
6ClusterGANNMI0.93—Unverified
7DMSCNMI0.93—Unverified
8DDCNMI0.92—Unverified
9JULE-RCNMI0.91—Unverified
10N2D (UMAP)NMI0.9—Unverified
#ModelMetricClaimedVerifiedStatus
1PRO-DSCAccuracy0.7—Unverified
2ITAEAccuracy0.68—Unverified
3SPICEAccuracy0.31—Unverified
4IMC-SwAV (Best)Accuracy0.28—Unverified
5IMC-SwAV (Avg+-)Accuracy0.28—Unverified
6C3Accuracy0.14—Unverified
7CCAccuracy0.14—Unverified
8MMDCAccuracy0.12—Unverified
9DCCMAccuracy0.11—Unverified
10DACAccuracy0.07—Unverified
#ModelMetricClaimedVerifiedStatus
1PRCut (DinoV2)Accuracy0.79—Unverified
2VMMAccuracy0.72—Unverified
3SPCAccuracy0.68—Unverified
4N2D (UMAP)Accuracy0.67—Unverified
5CoHiClustAccuracy0.65—Unverified
6DENAccuracy0.64—Unverified
7PSSCAccuracy0.63—Unverified
8GDLAccuracy0.63—Unverified
9DDCAccuracy0.62—Unverified
10DTI-ClusteringAccuracy0.61—Unverified
#ModelMetricClaimedVerifiedStatus
1TURTLE (CLIP + DINOv2)Accuracy72.9—Unverified
2MIM-Refiner (D2V2-ViT-H/14)Accuracy67.3—Unverified
3SeLaNMI66.4—Unverified
4PRO-DSCAccuracy65—Unverified
5MIM-Refiner (MAE-ViT-H/14)Accuracy64.6—Unverified