Contrastive Hierarchical Clustering |
CHC |
ECML PKDD 2023 |
Pytorch |
|
A Clustering Framework for Unsupervised and Semi-supervised New Intent Discovery |
USNID |
IEEE TKDE 2023 |
Pytorch |
|
Deep Multiview Clustering by Contrasting Cluster Assignments |
CVCL |
ICCV 2023 |
Pytorch |
|
Stable Cluster Discrimination for Deep Clustering |
SeCu |
ICCV 2023 |
- |
|
Cross-view Topology Based Consistent and Complementary Information for Deep Multi-view Clustering |
CTCC |
ICCV 2023 |
- |
|
Deep Multi-view Subspace Clustering with Anchor Graph |
DMCAG |
IJCAI 2023 |
- |
|
Incomplete Multi-view Clustering via Prototype-based Imputation |
ProImp |
IJCAI 2023 |
- |
|
CONGREGATE: Contrastive Graph Clustering in Curvature Spaces |
CONGREGATE |
IJCAI 2023 |
Pytorch |
|
Multi-level Graph Contrastive Prototypical Clustering |
MLG-CPC |
IJCAI 2023 |
- |
|
Dink-Net: Neural Clustering on Large Graphs |
Dink-Net |
ICML 2023 |
Pytorch |
|
Cluster-Guided Contrastive Graph Clustering Network |
CCGC |
AAAI 2023 |
Pytorch |
|
Hard Sample Aware Network for Contrastive Deep Graph Clustering |
HSAN |
AAAI 2023 |
Pytorch |
|
Dual Mutual Information Constraints for Discriminative Clustering |
DMICC |
AAAI 2023 |
Pytorch |
|
Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering |
SGDMC |
AAAI 2023 |
- |
|
Scalable Attributed-Graph Subspace Clustering |
SAGSC |
AAAI 2023 |
TensorFlow |
|
Semantic-Enhanced Image Clustering |
SIC |
AAAI 2023 |
- |
|
GLCC: A General Framework for Graph-Level Clustering |
GLCC |
AAAI 2023 |
- |
|
Highly Confident Local Structure Based Consensus Graph Learning for Incomplete Multi-View Clustering |
HCLS_CGL |
CVPR 2023 |
- |
|
Deep Incomplete Multi-view Clustering with Cross-view Partial Sample and Prototype Alignment |
IMVC |
CVPR 2023 |
- |
|
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering |
DeepMVC |
CVPR 2023 |
Pytorch |
|
DivClust: Controlling Diversity in Deep Clustering |
DivClust |
CVPR 2023 |
Pytorch |
|
SPICE: Semantic Pseudo-labeling for Image Clustering |
SPICE |
TIP 2022 |
Pytorch |
|
Generalised Mutual Information for Discriminative Clustering |
GEMINI |
NeurIPS 2022 |
- |
|
Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering |
SHGP |
NeurIPS 2022 |
Pytorch |
|
Learning Representation for Clustering via Prototype Scattering and Positive Sampling |
ProPos |
TPAMI 2022 |
Pytorch |
|
Dual Contrastive Prediction for Incomplete Multi-view Representation Learning |
DCP |
TPAMI 2022 |
Pytorch |
|
GOCA: Guided Online Cluster Assignment for Self-supervised Video Representation Learning |
GOCA |
ECCV 2022 |
Pytorch |
|
Fine-Grained Fashion Representation Learning by Online Deep Clustering |
MODC |
ECCV 2022 |
- |
|
Embedding Contrastive Unsupervised Features to Cluster In- and Out-of-distribution Noise in Corrupted Image Datasets |
SNCF |
ECCV 2022 |
Pytorch |
|
On Mitigating Hard Clusters for Face Clustering |
- |
ECCV 2022 |
Pytorch |
|
Deep Safe Incomplete Multi-view Clustering: Theorem and Algorithm |
DSIMVC |
ICML 2022 |
Pytorch |
|
Locally Normalized Soft Contrastive Clustering for Compact Clusters |
LNSCC |
IJCAI 2022 |
- |
|
Contrastive Multi-view Hyperbolic Hierarchical Clustering |
CMHHC |
IJCAI 2022 |
- |
|
EMGCF: Effcient Multi-view Graph Clustering with Comprehensive Fusion |
EMGCF |
IJCAI 2022 |
- |
|
Efficient Orthogonal Multi-view Subspace Clustering |
OMSC |
KDD 2022 |
MATLAB |
|
Clustering with Fair-Center Representation: Parameterized Approximation Algorithms and Heuristics |
- |
KDD 2022 |
- |
|
DeepDPM: Deep Clustering With an Unknown Number of Clusters |
DeepDPM |
CVPR 2022 |
Pytorch |
|
Unsupervised Action Segmentation by Joint Representation Learning and Online Clustering |
- |
CVPR 2022 |
- |
|
Efficient Deep Embedded Subspace Clustering |
EDESC |
CVPR 2022 |
Pytorch |
|
SLIC: Self-Supervised Learning With Iterative Clustering for Human Action Videos |
SLIC |
CVPR 2022 |
Pytorch |
|
MPC: Multi-View Probabilistic Clustering |
MPC |
CVPR 2022 |
- |
|
Deep Safe Multi-View Clustering: Reducing the Risk of Clustering Performance Degradation Caused by View Increase |
DSMVC |
CVPR 2022 |
- |
|
Discriminative Similarity for Data Clustering |
CDS |
ICLR 2022 |
- |
|
A Deep Variational Approach to Clustering Survival Data |
VaDeSC |
ICLR 2022 |
TensorFlow |
|
Contrastive Fine-grained Class Clustering via Generative Adversarial Networks |
C3-GAN |
ICLR 2022 |
Pytorch |
|
Deep Clustering of Text Representations for Supervision-Free Probing of Syntax |
SyntDEC |
AAAI 2022 |
- |
|
Deep Graph Clustering via Dual Correlation Reduction |
DCRN |
AAAI 2022 |
Pytorch |
|
Top-Down Deep Clustering with Multi-generator GANs |
HC-MGAN |
AAAI 2022 |
Pytorch |
|
Neural generative model for clustering by separating particularity and commonality |
DGC |
Information Sciences 2022 |
- |
|
Information Maximization Clustering via Multi-View Self-Labelling |
IMC-SwAV |
Knowledge-Based Systems 2022 |
Pytorch |
|
Sign prediction in sparse social networks using clustering and collaborative filtering |
- |
TJSC 2022 |
- |
|
You Never Cluster Alone |
TCC |
NeurIPS 2021 |
- |
|
Multi-Facet Clustering Variational Autoencoders |
MFCVAE |
NeurIPS 2021 |
Pytorch |
|
Multi-view Contrastive Graph Clustering |
MCGC |
NeurIPS 2021 |
Python |
|
Graph Contrastive Clustering |
GCC |
ICCV 2021 |
Pytorch |
|
One-pass Multi-view Clustering for Large-scale Data |
OPMC |
ICCV 2021 |
Matlab |
|
Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering |
Multi-VAE |
ICCV 2021 |
Pytorch |
|
Learn to Cluster Faces via Pairwise Classification |
- |
ICCV 2021 |
- |
|
Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos |
MCN |
ICCV 2021 |
Pytorch |
|
Clustering by Maximizing Mutual Information Across Views |
CRLC |
ICCV 2021 |
- |
|
End-to-End Robust Joint Unsupervised Image Alignment and Clustering |
Jim-Net |
ICCV 2021 |
- |
|
Learning Hierarchical Graph Neural Networks for Image Clustering |
Hi-LANDER |
ICCV 2021 |
Pytorch |
|
Deep Descriptive Clustering |
DDC |
IJCAI 2021 |
- |
|
Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces |
ACe/DeC |
IJCAI 2021 |
- |
|
Graph Debiased Contrastive Learning with Joint Representation Clustering |
GDCL |
IJCAI 2021 |
Pytorch |
|
Unsupervised Feature Learning by Cross-Level Instance-Group Discrimination |
CLD |
CVPR 2021 |
Pytorch |
|
Nearest Neighbor Matching for Deep Clustering |
NNM |
CVPR 2021 |
Pytorch |
|
Jigsaw Clustering for Unsupervised Visual Representation Learning |
JigsawClustering |
CVPR 2021 |
Pytorch |
|
COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction |
COMPLETER |
CVPR 2021 |
Pytorch |
|
Reconsidering Representation Alignment for Multi-view Clustering |
SiMVC & CoMVC |
CVPR 2021 |
Pytorch |
|
Double Low-rank Representation with Projection Distance Penalty for Clustering |
DLRRPD |
CVPR 2021 |
Matlab |
|
Improving Unsupervised Image Clustering With Robust Learning |
RUC |
CVPR 2021 |
Pytorch |
|
Learning a Self-Expressive Network for Subspace Clustering |
SENet |
CVPR 2021 |
Pytorch |
|
Clusformer: A Transformer Based Clustering Approach to Unsupervised Large-Scale Face and Visual Landmark Recognition |
Clusformer |
CVPR 2021 |
- |
|
Cluster-wise Hierarchical Generative Model for Deep Amortized Clustering |
CHiGac |
CVPR 2021 |
- |
|
Refining Pseudo Labels with Clustering Consensus over Generations for Unsupervised Object Re-identification |
RLCC |
CVPR 2021 |
- |
|
Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation |
IDFD |
ICLR 2021 |
Pytorch |
|
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering |
MiCE |
ICLR 2021 |
Pytorch |
|
Discovering New Intents with Deep Aligned Clustering |
DeepAligned |
AAAI 2021 |
Pytorch |
|
Contrastive Clustering |
CC |
AAAI 2021 |
Pytorch |
|
Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks |
RNNGCN |
AAAI 2021 |
Pytorch |
|
LRSC: Learning Representations for Subspace Clustering |
LRSC |
AAAI 2021 |
- |
|
Deep Fusion Clustering Network |
DFCN |
AAAI 2021 |
Pytorch |
|
Variational Deep Embedding Clustering by Augmented Mutual Information Maximization |
VCAMI |
ICPR 2021 |
- |
|
Supporting Clustering with Contrastive Learning |
SCCL |
NAACL 2021 |
Pytorch |
|
Pseudo-Supervised Deep Subspace Clustering |
PSSC |
TIP 2021 |
TensorFlow |
|
A hybrid approach for text document clustering using Jaya optimization algorithm |
HJO-DC |
ESWA 2021 |
- |
|
Deep video action clustering via spatio-temporal feature learning |
DVAC |
Neurocomputing 2021 |
- |
|
A new clustering method for the diagnosis of CoVID19 using medical images |
IGSA |
Applied Intelligence 2021 |
- |
|
A Decoder-Free Variational Deep Embedding for Unsupervised Clustering |
DFVC |
TNNLS 2021 |
- |
|
Image clustering using an augmented generative adversarial network and information maximization |
- |
TNNLS 2021 |
TensorFlow |
|
Learning the Precise Feature for Cluster Assignment |
- |
IEEE Trans Cybern 2021 |
TensorFlow |
|
Deep Subspace Clustering with Data Augmentation |
DSCwithDA |
NeurIPS 2020 |
Pytorch |
|
Deep Transformation-Invariant Clustering |
DTI |
NeurIPS 2020 |
Pytorch |
|
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments |
SwAV |
NeurIPS 2020 |
Pytorch |
|
Adversarial Learning for Robust Deep Clustering |
ALRDC |
NeurIPS 2020 |
Keras |
|
Self-supervised learning by cross-modal audio-video clustering |
XDC |
NeurIPS 2020 |
Pytorch |
|
Mitigating Embedding and Class Assignment Mismatch in Unsupervised Image Classification |
TSUC |
ECCV 2020 |
Pytorch |
|
GATCluster: Self-Supervised Gaussian-Attention Network for Image Clustering |
GATCluster |
ECCV 2020 |
Pytorch |
|
Deep Image Clustering with Category-Style Representation |
DCCS |
ECCV 2020 |
Pytorch |
|
MPCC: Matching Priors and Conditionals for Clustering |
MPCC |
ECCV 2020 |
Pytorch |
|
SCAN: Learning to Classify Images without Labels |
SCAN |
ECCV 2020 |
Pytorch |
|
Learning to Cluster under Domain Shift |
ACIDS |
ECCV 2020 |
Pytorch |
|
Multi-View Attribute Graph Convolution Networks for Clustering |
MAGCN |
IJCAI 2020 |
- |
|
CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network |
CDIMC-net |
IJCAI 2020 |
- |
|
Spectral Clustering with Graph Neural Networks for Graph Pooling |
- |
ICML 2020 |
TensorFlow |
|
Variational Clustering: Leveraging Variational Autoencoders for Image Clustering |
- |
IJCNN 2020 |
- |
|
Improving k-Means Clustering Performance with Disentangled Internal Representations |
Annealing SNNL |
IJCNN 2020 |
Pytorch |
|
Unsupervised clustering through gaussian mixture variational autoencoder with non-reparameterized variational inference and std annealing |
NVISA |
IJCNN 2020 |
- |
|
Learning to Cluster Faces via Confidence and Connectivity Estimation |
LTC v2 |
CVPR 2020 |
Pytorch |
|
Density-Aware Feature Embedding for Face Clustering |
DA-Net |
CVPR 2020 |
- |
|
Deep Semantic Clustering by Partition Confidence Maximisation |
PICA |
CVPR 2020 |
Pytorch |
|
Online Deep Clustering for Unsupervised Representation Learning |
ODC |
CVPR 2020 |
Pytorch |
|
Multi-Scale Fusion Subspace Clustering Using Similarity Constraint |
SC-MSFSC |
CVPR 2020 |
- |
|
Unsupervised Clustering using Pseudo-semi-supervised Learning |
Kingdra |
ICLR 2020 |
Keras |
|
Self-labelling via Simultaneous Clustering and Representation Learning |
SeLa |
ICLR 2020 |
Pytorch |
|
Structural Deep Clustering Network |
SDCN |
WWW 2020 |
Pytorch |
|
Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement |
CDAC+ |
AAAI 2020 |
Pytorch |
|
Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering |
UGLTL |
AAAI 2020 |
- |
|
Multi-View Clustering in Latent Embedding Space |
MCLES |
AAAI 2020 |
MATLAB |
|
Hierarchically Clustered Representation Learning |
HCRL |
AAAI 2020 |
- |
|
Adaptive Two-Dimensional Embedded Image Clustering |
A2DEIC |
AAAI 2020 |
- |
|
Learning to cluster documents into workspaces using large scale activity logs |
- |
SIGKDD 2020 |
- |
|
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding |
N2D |
ICPR 2020 |
TensorFlow |
|
A text document clustering method based on weighted Bert model |
- |
ITNEC 2020 |
- |
|
Deep clustering: On the link between discriminative models and K-means |
SoftK-means |
TPAMI 2020 |
Theano |
|
Efficient and Effective Regularized Incomplete Multi-View Clustering |
EE-IMVC |
TPAMI 2020 |
- |
|
Adversarial Deep Embedded Clustering: on a better trade-off between Feature Randomness and Feature Drift |
ADEC |
TKDE 2020 |
- |
|
Schain-iram: An efficient and effective semi-supervised clustering algorithm for attributed heterogeneous information networks |
SCHAIN-IRAM |
TKDE 2020 |
- |
|
Image Clustering via Deep Embedded Dimensionality Reduction and Probability-Based Triplet Loss |
DERC |
TIP 2020 |
TensorFlow |
|
Deep Clustering with a Dynamic Autoencoder: From Reconstruction Towards Centroids Construction |
DynAE |
Neural Networks 2020 |
TensorFlow |
|
Spectral Clustering via Ensemble Deep Autoencoder Learning (SC-EDAE) |
SC-EDAE |
PR 2020 |
- |
|
Cross multi-type objects clustering in attributed heterogeneous information network |
CMOC-AHIN |
KBS 2020 |
- |
|
Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis |
ItClust |
Nature machine intelligence 2020 |
Keras |
|
Optimal Sampling and Clustering in the Stochastic Block Model |
- |
NeurIPS 2019 |
Python |
|
Selective Sampling-based Scalable Sparse Subspace Clustering |
S5C |
NeurIPS 2019 |
MATLAB |
|
GEMSEC: Graph Embedding with Self Clustering |
GEMSEC |
ASONAM 2019 |
TensorFlow |
|
Video Face Clustering with Unknown Number of Clusters |
BCL |
ICCV 2019 |
Pytorch |
|
ClusterSLAM: A SLAM Backend for Simultaneous Rigid Body |
ClusterSLAM |
ICCV 2019 |
- |
|
Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embedding |
DGG |
ICCV 2019 |
Pytorch |
|
Deep Comprehensive Correlation Mining for Image Clustering |
DCCM |
ICCV 2019 |
Pytorch |
|
Invariant Information Clustering for Unsupervised Image Classification and Segmentation |
IIC |
ICCV 2019 |
Pytorch |
|
Subspace Structure-aware Spectral Clustering for Robust Subspace Clustering |
- |
ICCV 2019 |
- |
|
Is an Affine Constraint Needed for Affine Subspace Clustering? |
- |
ICCV 2019 |
- |
|
Deep Spectral Clustering using Dual Autoencoder Network |
- |
ICCV 2019 |
Tensorflow |
|
Learning to Discover Novel Visual Categories via Deep Transfer Clustering |
DTC |
ICCV 2019 |
Pytorch |
|
Reciprocal Multi-Layer Subspace Learning for Multi-View Clustering |
RMSL |
ICCV 2019 |
- |
|
Adversarial Graph Embedding for Ensemble Clustering |
AGAE |
IJCAI 2019 |
- |
|
Attributed Graph Clustering: A Deep Attentional Embedding Approach |
DAEGC |
IJCAI 2019 |
- |
|
Neural Collaborative Subspace Clustering |
- |
ICML 2019 |
- |
|
Self-Supervised Convolutional Subspace Clustering Network |
S^2ConvSCN |
CVPR 2019 |
- |
|
Balanced Self-Paced Learning for Generative Adversarial Clustering Network |
ClusterGAN |
CVPR 2019 |
- |
|
Linkage-based Face Clustering via Graph Convolution Network |
L-GCN |
CVPR 2019 |
Pytorch |
|
Learning to Cluster Faces on an Affinity Graph |
LTC |
CVPR 2019 |
Pytorch |
|
Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering |
LTVAE |
ICLR 2019 |
Pytorch |
|
Clustering Meets Implicit Generative Models |
- |
ICLR 2019 workshop |
- |
|
ClusterGAN: Latent Space Clustering in Generative Adversarial Networks |
ClusterGAN |
AAAI 2019 |
TensorFlow |
|
Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks |
Cluster-GCN |
SIGKDD 2019 |
TensorFlow |
|
Adaptive Self-paced Deep Clustering with Data Augmentation |
ASPC-DA |
TKDE 2019 |
TensorFlow |
|
Clustering with outlier removal |
COR |
TKDE 2019 |
- |
|
Clustering single-cell RNA-seq data with a model-based deep learning approach |
scDeepCluster |
Nature Machine Intelligence 2019 |
Keras |
|
A Hybrid Autoencoder Network for Unsupervised Image Clustering |
- |
Algorithms 2019 |
- |
|
A Deep Clustering Algorithm based on Gaussian Mixture Model |
- |
JPCS 2019 |
- |
|
Text document clustering using spectral clustering algorithm with particle swarm optimization |
SCPSO |
ESWA 2019 |
Python |
|
Deep Clustering with Convolutional Autoencoders |
DCEC |
ICONIP 2018 |
Keras |
|
RDEC: Integrating Regularization into Deep Embedded Clustering for Imbalanced Datasets |
RDEC |
ACML 2018 |
- |
|
Deep Embedded Clustering with Data Augmentation |
DEC-DA |
ACML 2018 |
TensorFlow |
|
Deep adversarial subspace clustering |
DASC |
CVPR 2018 |
- |
|
Deep Clustering for Unsupervised Learning of Visual Features |
DeepCluster |
ECCV 2018 |
Pytorch |
|
SpectralNet: Spectral Clustering Using Deep Neural Networks |
SpectralNet |
ICLR 2018 |
TensorFlow PyTorch |
|
Mixture of GANs for Clustering |
- |
IJCAI 2018 |
- |
|
Subspace Clustering using a Low-rank Constrained Autoencoder |
LRAE |
Information Science 2018 |
- |
|
Deep Discriminative Latent Space for Clustering |
- |
NeurIPS 2017 |
- |
|
Deep Subspace Clustering Networks |
DSC-Nets |
NeurIPS 2017 |
TensorFlow |
|
Is Simple Better?: Revisiting Simple Generative Models for Unsupervised Clustering |
- |
NeurIPS 2017 Workshop |
Pytorch |
|
Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization |
DEPICT |
ICCV 2017 |
Theano |
|
Deep Adaptive Image Clustering |
DAC |
ICCV 2017 |
Keras |
|
Improved Deep Embedded Clustering with Local Structure Preservation |
IDEC |
IJCAI 2017 |
Keras Pytorch |
|
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering |
VaDE |
IJCAI 2017 |
Keras |
|
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering |
DCN |
ICML 2017 |
Theano |
|
Learning Discrete Representations via Information Maximizing Self-Augmented Training |
IMSAT |
ICML 2017 |
Python |
|
Deep Unsupervised Clustering With Gaussian Mixture Variational AutoEncoders |
GMVAE |
ICLR 2017 |
Lua |
|
Semi-supervised clustering in attributed heterogeneous information networks |
SCHAIN |
WWW 2017 |
MATLAB |
|
Cascade Subspace Clustering |
CSC |
AAAI 2017 |
- |
|
Unsupervised Multi-Manifold Clustering by Learning Deep Representation |
DMC |
AAAI 2017 Workshop |
- |
|
Combining structured node content and topology information for networked graph clustering |
- |
TKDD 2017 |
- |
|
CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data |
- |
TMM 2017 |
- |
|
Robust continuous clustering |
RCC |
PNAS 2017 |
- |
|
Unsupervised Deep Embedding for Clustering Analysis |
DEC |
ICML 2016 |
Caffe TensorFlow |
|
Joint Unsupervised Learning of Deep Representations and Image Clusters |
JULE |
CVPR 2016 |
Torch |
|
Deep subspace clustering with sparsity prior |
PARTY |
IJCAI 2016 |
- |
|
CCCF: Improving collaborative filtering via scalable user-item co-clustering |
CCCF |
WSDM 2016 |
- |
|
Deep Embedding Network for Clustering |
DEN |
ICPR 2014 |
- |
|
Learning Deep Representations for Graph Clustering |
- |
AAAI 2014 |
Python |
|
Auto-encoder Based Data Clustering |
ABDC |
CIARP 2013 |
Pytorch |
|
Discriminative Clustering by Regularized Information Maximization |
RIM |
NeurIPS 2010 |
- |
|