| You Never Cluster Alone |
TCC |
NeurIPS 2021 |
- |
| Multi-Facet Clustering Variational Autoencoders |
MFCVAE |
NeurIPS 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 |
| 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 |
- |
| 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 |
- |
| Prototypical Contrastive Learning of Unsupervised Representations |
PCL |
ICLR 2021 |
Pytorch |
| Contrastive Clustering |
CC |
AAAI2021 |
Pytorch |
| Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation |
IDFD |
ICLR2021 |
Pytorch |
| MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering |
MiCE |
ICLR2021 |
Pytorch |
| Deep clustering with a Dynamic Autoencoder: From reconstruction towards centroids construction |
DynAE |
NN 2020 |
TensorFlow |
| Adversarial Deep Embedded Clustering: on a better trade-off between Feature Randomness and Feature Drift |
ADEC |
TKDE 2020 |
- |
| Mitigating Embedding and Class Assignment Mismatch in Unsupervised Image Classification |
TSUC |
ECCV 2020 |
Pytorch |
| Variational Clustering: Leveraging Variational Autoencoders for Image Clustering |
- |
IJCNN 2020 |
- |
| 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 |
| Deep Subspace Clustering with Data Augmentation |
DSCwithDA |
NIPS2020 |
Pytorch |
| SCAN: Learning to Classify Images without Labels |
SCAN |
ECCV2020 |
Pytorch |
| Deep Transformation-Invariant Clustering |
DTI |
NIPS2020 |
Pytorch |
| Unsupervised Learning of Visual Features by Contrasting Cluster Assignments |
SwAV |
NIPS2020 |
PyTorch |
| Adversarial Learning for Robust Deep Clustering |
ALRDC |
NIPS 2020 |
Keras |
| Learning to Cluster under Domain Shift |
ACIDS |
ECCV 2020 |
Pytorch |
| Deep Semantic Clustering by Partition Confidence Maximisation |
PICA |
CVPR 2020 |
Pytorch |
| Online Deep Clustering for Unsupervised Representation Learning |
ODC |
CVPR 2020 |
Python |
| Improving k-Means Clustering Performance with Disentangled Internal Representations |
Annealing SNNL |
IJCNN 2020 |
PyTorch |
| N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding. |
N2D |
ICPR 2020 |
TensorFlow |
| Unsupervised Clustering using Pseudo-semi-supervised Learning |
Kingdra |
ICLR 2020 |
Keras |
| Spectral Clustering with Graph Neural Networks for Graph Pooling |
- |
ICML 2020 |
TensorFlow |
| Self-labelling via simultaneous clustering and representation learning |
SeLa |
ICLR2020 |
Pytorch |
| Deep clustering: On the link between discriminative models and K-means |
SoftK-means |
TPAMI 2020 |
Python |
| Image Clustering via Deep Embedded Dimensionality Reduction and Probability-Based Triplet Loss |
DERC |
TIP2020 |
TensorFlow |
| Structural Deep Clustering Network |
SDCN |
WWW 2020 |
Pytorch |
| Attributed Graph Clustering: A Deep Attentional Embedding Approach |
DAEGC |
IJCAI 2019 |
|
| Optimal Sampling and Clustering in the Stochastic Block Model |
|
NIPS 2019 |
Python |
| Selective Sampling-based Scalable Sparse Subspace Clustering |
S5C |
NIPS 2019 |
MATLAB |
| Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering |
LTVAE |
ICLR 2019 |
Pytorch |
| Balanced Self-Paced Learning for Generative Adversarial Clustering Network |
ClusterGAN |
CVPR2019 |
|
| Adaptive Self-paced Deep Clustering with Data Augmentation |
ASPC-DA |
TKDE 2019 |
TensorFlow |
| Learning to Cluster Faces on an Affinity Graph |
LTC |
CVPR 2019 |
Pytorch |
| 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 |
|
| GEMSEC: Graph Embedding with Self Clustering |
GEMSEC |
ASONAM 2019 |
TensorFlow |
| ClusterGAN: Latent Space Clustering in Generative Adversarial Networks |
ClusterGAN |
AAAI 2019 |
TensorFlow |
| Adversarial Graph Embedding for Ensemble Clustering |
AGAE |
IJCAI 2019 |
|
| A Hybrid Autoencoder Network for Unsupervised Image Clustering |
|
Algorithms 2019 |
|
| A Deep Clustering Algorithm based on Gaussian Mixture Model |
|
Journal of Physics: Conference Series 2019 |
|
| Clustering Meets Implicit Generative Models |
|
ICLR 2019 workshop |
|
| Deep Embedded Clustering with Data Augmentation |
DEC-DA |
ACML 2018 |
TensorFlow |
| Deep Clustering for Unsupervised Learning of Visual Features |
DeepCluster |
ECCV 2018 |
Pytorch |
| Deep Clustering with Convolutional Autoencoders |
DCEC |
ICONIP 2018 |
Keras |
| SpectralNet: Spectral Clustering Using Deep Neural Networks |
SpectralNet |
ICLR 2018 |
TensorFlow |
| Subspace clustering using a low-rank constrained autoencoder |
LRAE |
Information Science 2018 |
|
| Unsupervised Multi-Manifold Clustering by Learning Deep Representation |
DMC |
AAAI 2017 Workshop |
|
| Deep Discriminative Latent Space for Clustering |
|
NIPS 2017 |
|
| Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering |
DCN |
PMLR 2017 |
Theano |
| Deep Unsupervised Clustering With Gaussian Mixture Variational AutoEncoders |
GMVAE |
ICLR 2017 |
Lua |
| Is Simple Better?: Revisiting Simple Generative Models for Unsupervised Clustering |
|
NIPS 2017 Workshop |
Pytorch |
| Improved Deep Embedded Clustering with Local Structure Preservation |
IDEC |
IJCAI 2017 |
Keras Pytorch |
| Deep Clustering via joint convolutional autoencoder embedding and relative entropy minimization |
DEPICT |
ICCV 2017 |
Theano |
| Deep Adaptive Image Clustering |
DAC |
ICCV 2017 |
Keras |
| Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering |
VaDE |
IJCAI 2017 |
Keras |
| Deep Subspace Clustering Networks |
DSC-Nets |
NIPS 2017 |
TensorFlow |
| CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data |
|
IEEE Transactions on Multimedia 2017 |
|
| Learning Discrete Representations via Information Maximizing Self-Augmented Training |
IMSAT |
ICML 2017 |
Python |
| Unsupervised Deep Embedding for Clustering Analysis |
DEC |
ICML 2016 |
Caffe TensorFlow |
| Joint Unsupervised Learning of Deep Representations and Image Clustering |
JULE |
CVPR 2016 |
Torch |
| 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 |
NIPS 2010 |
|