# DeepClustering

**Repository Path**: silent790/DeepClustering

## Basic Information

- **Project Name**: DeepClustering
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-05-17
- **Last Updated**: 2022-05-17

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Deep Clustering: methods and implements

### We are preparing a survey on deep clustering with more detailed induction and analysis, it will be released soon!

|    Survey Paper    |  Conference  |  Code |
|  :---------  | :------:  | :------: |
| [A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8412085) | IEEE ACCESS 2018  | - |
| [Clustering with Deep Learning: Taxonomy and New Methods](https://arxiv.org/pdf/1801.07648.pdf) | Arxiv 2018 | [Theano](https://github.com/elieJalbout/Clustering-with-Deep-learning) |


|    Pre-print Paper    |  Method  |  Conference  |  Code |
|  :---------  | :------:  | :------: | :------: |
| [Deep Clustering and Representation Learning with Geometric Structure Preservation](https://arxiv.org/abs/2009.09590) | DCRL | Arxiv 2021 | [Pytorch](https://github.com/LirongWu/GCML) |
| [Deep Clustering with Self-supervision using Pairwise Data Similarities](https://www.techrxiv.org/articles/preprint/Deep_Clustering_with_Self-supervision_using_Pairwise_Data_Similarities/14852652) | DCSS | TechRxiv 2021 | [Pytorch](https://github.com/Armanfard-Lab/DCSS/blob/main/Codes/train.py) |
| [SPICE: Semantic Pseudo-labeling for Image Clustering](https://arxiv.org/pdf/2103.09382v1.pdf) | SPICE | Arxiv 2021 | [Pytorch](https://github.com/niuchuangnn/SPICE) |
| [DHOG: Deep Hierarchical Object Grouping](https://arxiv.org/pdf/2003.08821.pdf) | DHOG | Arxiv 2020 | - |
| [Deep Robust Clustering by Contrastive Learning](https://arxiv.org/abs/2008.03030) | DRC | Arxiv 2020 | - |
| [Un-Mix: Rethinking Image Mixture for Unsupervised Visual Representation Learning](https://arxiv.org/pdf/2003.05438.pdf) | Un-Mix | Arxiv 2020 | [Pytorch](https://github.com/szq0214/Un-Mix) |
| [Differentiable Deep Clustering with Cluster Size Constraints](https://arxiv.org/pdf/1910.09036.pdf) |  -  | Arxiv 2019 | - |
| [Deep Continuous Clustering](https://arxiv.org/pdf/1803.01449.pdf) |  DCC  | Arxiv 2018 | [Pytorch](https://github.com/shahsohil/DCC) |
| [Clustering-driven Deep Embedding with Pairwise Constraints](https://arxiv.org/pdf/1803.08457.pdf) |  CPAC  | Arxiv 2018 |  [Pytorch](https://github.com/sharonFogel/CPAC) |
| [Deep Temporal Clustering : Fully Unsupervised Learning of Time-Domain Features](https://arxiv.org/abs/1802.01059) | DTC | Arxiv 2018 | [Keras](https://github.com/FlorentF9/DeepTemporalClustering) |
| [Graph Clustering with Dynamic Embedding](https://arxiv.org/pdf/1712.08249.pdf) | GRACE | Arxiv 2017 | - |
| [Deep Unsupervised Clustering using Mixture of Autoencoders](https://arxiv.org/pdf/1712.07788.pdf) | MIXAE | Arxiv 2017 | - |
| [Discriminatively Boosted Image Clustering with Fully Convolutional Auto-Encoders](https://arxiv.org/pdf/1703.07980.pdf) | DBC | Arxiv 2017 | - |
| [Deep Clustering Network](https://arxiv.org/pdf/1610.04794v1.pdf) |  DCN  | Arxiv 2016 | [Theano](https://github.com/boyangumn/DCN-New) |



|    Paper    |  Method |  Conference |  Code |
|  :---------  | :------:  | :------: | :------: |
| [Discriminative Similarity for Data Clustering](https://openreview.net/pdf?id=kj0_45Y4r9i) | CDS | ICLR 2022 | - |
| [A Deep Variational Approach to Clustering Survival Data](https://openreview.net/pdf?id=RQ428ZptQfU) | VaDeSC | ICLR 2022 | [TensorFlow](https://github.com/i6092467/vadesc) |
| [Contrastive Fine-grained Class Clustering via Generative Adversarial Networks](https://openreview.net/pdf?id=XWODe7ZLn8f) | C3-GAN | ICLR 2022 | [Pytorch](https://github.com/naver-ai/c3-gan) |
| [Ada-nets: Face Clustering via Adaptive Neighbour Discovery in the Structure Space](https://arxiv.org/pdf/2202.03800) | Ada-NETS | ICLR 2022 | [Pytorch](https://github.com/damo-cv/Ada-NETS) |
| [Deep Graph Clustering via Dual Correlation Reduction](https://arxiv.org/pdf/2112.14772.pdf) | DCRN | AAAI 2022 | [Pytorch](https://github.com/yueliu1999/DCRN) |
| [Top-Down Deep Clustering with Multi-generator GANs](https://arxiv.org/pdf/2112.03398.pdf) | HC-MGAN | AAAI 2022 | [Pytorch](https://github.com/dmdmello/HC-MGAN) |
| [You Never Cluster Alone](https://arxiv.org/abs/2106.01908) | TCC | NeurIPS 2021 | - |
| [Multi-Facet Clustering Variational Autoencoders](https://arxiv.org/pdf/2106.05241.pdf) | MFCVAE | NeurIPS 2021 | [Pytorch](https://github.com/FabianFalck/mfcvae) |
| [Multi-view Contrastive Graph Clustering](https://openreview.net/pdf?id=NlB8_hXkbby) | MCGC | NeurIPS 2021 | [Python](https://github.com/Panern/MCGC) |
| [Graph Contrastive Clustering](https://openaccess.thecvf.com/content/ICCV2021/papers/Zhong_Graph_Contrastive_Clustering_ICCV_2021_paper.pdf) | GCC | ICCV 2021 | [Pytorch](https://github.com/mynameischaos/GCC) |
| [One-pass Multi-view Clustering for Large-scale Data](https://openaccess.thecvf.com/content/ICCV2021/papers/Liu_One-Pass_Multi-View_Clustering_for_Large-Scale_Data_ICCV_2021_paper.pdf) | OPMC | ICCV 2021 | [Matlab](https://github.com/liujiyuan13/OPMC-code_release) |
| [Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering](https://openaccess.thecvf.com/content/ICCV2021/papers/Xu_Multi-VAE_Learning_Disentangled_View-Common_and_View-Peculiar_Visual_Representations_for_Multi-View_ICCV_2021_paper.pdf) | Multi-VAE | ICCV 2021 | [Pytorch](https://github.com/SubmissionsIn/Multi-VAE) |
| [Learn to Cluster Faces via Pairwise Classification](https://openaccess.thecvf.com/content/ICCV2021/papers/Liu_Learn_To_Cluster_Faces_via_Pairwise_Classification_ICCV_2021_paper.pdf) | - | ICCV 2021 | - |
| [Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos](https://arxiv.org/pdf/2104.12671.pdf) | MCN | ICCV 2021 | [Pytorch](https://github.com/brian7685/Multimodal-Clustering-Network) |
| [Clustering by Maximizing Mutual Information Across Views](https://arxiv.org/abs/2107.11635) | CRLC | ICCV 2021 | - |
| [End-to-End Robust Joint Unsupervised Image Alignment and Clustering](https://openaccess.thecvf.com/content/ICCV2021/papers/Zeng_End-to-End_Robust_Joint_Unsupervised_Image_Alignment_and_Clustering_ICCV_2021_paper.pdf) | Jim-Net | ICCV 2021| - |
| [Learning Hierarchical Graph Neural Networks for Image Clustering](https://openaccess.thecvf.com/content/ICCV2021/papers/Xing_Learning_Hierarchical_Graph_Neural_Networks_for_Image_Clustering_ICCV_2021_paper.pdf) | Hi-LANDER | ICCV 2021 | [Pytorch](https://github.com/dmlc/dgl/tree/master/examples/pytorch/hilander) |
| [Deep Descriptive Clustering](https://arxiv.org/pdf/2105.11549.pdf) | DDC | IJCAI 2021 | - |
| [Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces](https://www.ijcai.org/proceedings/2021/0389.pdf) | ACe/DeC | IJCAI 2021 | - |
| [Graph Debiased Contrastive Learning with Joint Representation Clustering](https://www.ijcai.org/proceedings/2021/0473.pdf) | GDCL | IJCAI 2021 | [Pytorch](https://github.com/hzhao98/GDCL) |
| [Unsupervised Feature Learning by Cross-Level Instance-Group Discrimination](http://people.eecs.berkeley.edu/~xdwang/papers/CLD.pdf) | CLD | CVPR 2021 | [Pytorch](https://github.com/frank-xwang/CLD-UnsupervisedLearning) |
| [Nearest Neighbor Matching for Deep Clustering](https://openaccess.thecvf.com/content/CVPR2021/html/Dang_Nearest_Neighbor_Matching_for_Deep_Clustering_CVPR_2021_paper.html) | NNM | CVPR 2021 | [Pytorch](https://github.com/ZhiyuanDang/NNM) |
| [Jigsaw Clustering for Unsupervised Visual Representation Learning](https://openaccess.thecvf.com/content/CVPR2021/html/Chen_Jigsaw_Clustering_for_Unsupervised_Visual_Representation_Learning_CVPR_2021_paper.html) | JigsawClustering | CVPR 2021 | [Pytorch](https://github.com/dvlab-research/JigsawClustering) |
| [COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction](https://openaccess.thecvf.com/content/CVPR2021/html/Lin_COMPLETER_Incomplete_Multi-View_Clustering_via_Contrastive_Prediction_CVPR_2021_paper.html) | COMPLETER | CVPR 2021 | [Pytorch](https://github.com/XLearning-SCU/2021-CVPR-Completer) |
| [Reconsidering Representation Alignment for Multi-view Clustering](https://openaccess.thecvf.com/content/CVPR2021/html/Trosten_Reconsidering_Representation_Alignment_for_Multi-View_Clustering_CVPR_2021_paper.html) | SiMVC & CoMVC | CVPR 2021 | [Pytorch](https://github.com/DanielTrosten/mvc) |
| [Double Low-rank Representation with Projection Distance Penalty for Clustering](https://github.com/fuzhiqiang1230/DLRRPD/blob/main/8382_Double_low_rank_representation_with_projection_distance_penalty_for_clustering.pdf) | DLRRPD | CVPR 2021 | [Matlab](https://github.com/fuzhiqiang1230/DLRRPD) |
| [Improving Unsupervised Image Clustering With Robust Learning](https://arxiv.org/pdf/2012.11150.pdf) | RUC | CVPR 2021 | [Pytorch](https://github.com/deu30303/RUC) |
| [Learning a Self-Expressive Network for Subspace Clustering](https://openaccess.thecvf.com/content/CVPR2021/html/Zhang_Learning_a_Self-Expressive_Network_for_Subspace_Clustering_CVPR_2021_paper.html) | SENet | CVPR 2021 | [Pytorch](https://github.com/zhangsz1998/self-expressive-network) |
| [Clusformer: A Transformer Based Clustering Approach to Unsupervised Large-Scale Face and Visual Landmark Recognition](https://openaccess.thecvf.com/content/CVPR2021/papers/Nguyen_Clusformer_A_Transformer_Based_Clustering_Approach_to_Unsupervised_Large-Scale_Face_CVPR_2021_paper.pdf) | Clusformer | CVPR 2021 | - |
| [Cluster-wise Hierarchical Generative Model for Deep Amortized Clustering](https://openaccess.thecvf.com/content/CVPR2021/html/Liu_Cluster-Wise_Hierarchical_Generative_Model_for_Deep_Amortized_Clustering_CVPR_2021_paper.html) | CHiGac | CVPR 2021 | - |
| [Refining Pseudo Labels with Clustering Consensus over Generations for Unsupervised Object Re-identification](https://openaccess.thecvf.com/content/CVPR2021/html/Zhang_Refining_Pseudo_Labels_With_Clustering_Consensus_Over_Generations_for_Unsupervised_CVPR_2021_paper.html) | RLCC | CVPR 2021 | - |
| [Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation](https://openreview.net/pdf?id=e12NDM7wkEY) | IDFD | ICLR 2021 | [Pytorch](https://github.com/TTN-YKK/Clustering_friendly_representation_learning) |
| [MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering](https://openreview.net/pdf?id=gV3wdEOGy_V) | MiCE | ICLR 2021 | [Pytorch](https://github.com/TsungWeiTsai/MiCE) |
| [Contrastive Clustering](https://arxiv.org/pdf/2009.09687.pdf) | CC | AAAI 2021 | [Pytorch](https://github.com/Yunfan-Li/Contrastive-Clustering) |
| [Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks](https://www.aaai.org/AAAI21Papers/AAAI-833.YaoY.pdf) | RNNGCN | AAAI 2021 | [Pytorch](https://github.com/InterpretableClustering/InterpretableClustering) |
| [LRSC: Learning Representations for Subspace Clustering](https://www.aaai.org/AAAI21Papers/AAAI-2600.LiC.pdf) | LRSC | AAAI 2021 | - |
| [Deep Fusion Clustering Network](https://arxiv.org/pdf/2012.09600.pdf) | DFCN | AAAI 2021 | [Pytorch](https://github.com/WxTu/DFCN) |
| [Pseudo-Supervised Deep Subspace Clustering](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9440402) | PSSC | TIP 2021 | [TensorFlow](https://github.com/sckangz/SelfsupervisedSC) |
| [Deep Subspace Clustering with Data Augmentation](https://proceedings.neurips.cc/paper/2020/hash/753a043674f0193523abc1bbce678686-Abstract.html) | DSCwithDA | NeurIPS 2020 | [Pytorch](https://github.com/mahdiabavisani/DSCwithDA) |
| [Deep Transformation-Invariant Clustering](https://arxiv.org/abs/2006.11132) | DTI | NeurIPS 2020 | [Pytorch](https://github.com/monniert/dti-clustering) |
| [Unsupervised Learning of Visual Features by Contrasting Cluster Assignments](https://arxiv.org/pdf/2006.09882.pdf)| SwAV | NeurIPS 2020 | [Pytorch](https://github.com/facebookresearch/swav) |
| [Adversarial Learning for Robust Deep Clustering](https://proceedings.neurips.cc/paper/2020/hash/6740526b78c0b230e41ae61d8ca07cf5-Abstract.html) | ALRDC | NeurIPS 2020 | [Keras](https://github.com/xdxuyang/ALRDC) |
| [Mitigating Embedding and Class Assignment Mismatch in Unsupervised Image Classification](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123690749.pdf) | TSUC | ECCV 2020 | [Pytorch](https://github.com/dscig/TwoStageUC) |
| [GATCluster: Self-Supervised Gaussian-Attention Network for Image Clustering](https://arxiv.org/pdf/2002.11863.pdf) | GATCluster | ECCV 2020 | [Pytorch](https://github.com/niuchuangnn/GATCluster) |
| [Deep Image Clustering with Category-Style Representation](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590052.pdf) | DCCS | ECCV 2020 | [Pytorch](https://github.com/sKamiJ/DCCS) |
| [MPCC: Matching Priors and Conditionals for Clustering](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123680647.pdf) | MPCC | ECCV 2020 | [Pytorch](https://github.com/jumpynitro/MPCC) |
| [SCAN: Learning to Classify Images without Labels](https://arxiv.org/abs/2005.12320) | SCAN | ECCV 2020 | [Pytorch](https://github.com/wvangansbeke/Unsupervised-Classification) |
| [Learning to Cluster under Domain Shift](https://arxiv.org/abs/2008.04646) | ACIDS | ECCV 2020 | [Pytorch](https://github.com/willi-menapace/acids-clustering-domain-shift) |
| [Multi-View Attribute Graph Convolution Networks for Clustering](https://www.ijcai.org/proceedings/2020/0411.pdf) | MAGCN | IJCAI 2020 | - |
| [CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network](https://www.ijcai.org/Proceedings/2020/0447.pdf) | CDIMC-net | IJCAI 2020 | - |
| [Spectral Clustering with Graph Neural Networks for Graph Pooling](https://arxiv.org/pdf/1907.00481.pdf)  |  -  |  ICML 2020  | [TensorFlow](https://github.com/FilippoMB/b∫bSpectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling)|
| [Variational Clustering: Leveraging Variational Autoencoders for Image Clustering](https://arxiv.org/pdf/2005.04613) | - | IJCNN 2020 | - |
| [Improving k-Means Clustering Performance with Disentangled Internal Representations](https://arxiv.org/abs/2006.04535) | Annealing SNNL |  IJCNN 2020 | [Pytorch](https://github.com/afagarap/pt-clustering-ae/) |
| [Deep Semantic Clustering by Partition Confidence Maximisation](https://raymond-sci.github.io/assets/project/huang2020pica/paper.pdf) | PICA | CVPR 2020 | [Pytorch](https://github.com/Raymond-sci/PICA) |
| [Online Deep Clustering for Unsupervised Representation Learning](https://arxiv.org/abs/2006.10645v1) | ODC | CVPR 2020 | [Pytorch](https://github.com/open-mmlab/OpenSelfSup) |
| [Multi-Scale Fusion Subspace Clustering Using Similarity Constraint](https://openaccess.thecvf.com/content_CVPR_2020/papers/Dang_Multi-Scale_Fusion_Subspace_Clustering_Using_Similarity_Constraint_CVPR_2020_paper.pdf) | SC-MSFSC | CVPR 2020 | - |
| [Unsupervised Clustering using Pseudo-semi-supervised Learning](https://openreview.net/pdf?id=rJlnxkSYPS) | Kingdra | ICLR 2020 | [Keras](https://github.com/divamgupta/deep-clustering-kingdra) |
| [Self-labelling via Simultaneous Clustering and Representation Learning](https://arxiv.org/pdf/1911.05371.pdf)  | SeLa |ICLR 2020| [Pytorch](https://github.com/yukimasano/self-label)|
| [Structural Deep Clustering Network](https://arxiv.org/abs/2002.01633) | SDCN | WWW 2020 | [Pytorch](https://github.com/461054993/SDCN) |
| [Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering](https://ojs.aaai.org/index.php/AAAI/article/view/6109) | UGLTL | AAAI 2020 | - |
| [Multi-View Clustering in Latent Embedding Space](https://ojs.aaai.org/index.php/AAAI/article/view/5756) | MCLES | AAAI 2020 | [MATLAB](https://github.com/ManshengChen/MCLES) |
| [Hierarchically Clustered Representation Learning](https://ojs.aaai.org/index.php/AAAI/article/view/6034) | HCRL | AAAI 2020 | - |
| [Adaptive Two-Dimensional Embedded Image Clustering](https://ojs.aaai.org/index.php/AAAI/article/view/5914) | A2DEIC | AAAI 2020 | - |
| [N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding](https://arxiv.org/abs/1908.05968) | N2D | ICPR 2020 | [TensorFlow](https://github.com/rymc/n2d) |
| [Deep clustering: On the link between discriminative models and K-means](https://arxiv.org/abs/1810.04246) | SoftK-means | TPAMI 2020 | [Theano](https://github.com/MOhammedJAbi/SoftKMeans) |
| [Efficient and Effective Regularized Incomplete Multi-View Clustering](https://ieeexplore.ieee.org/abstract/document/9001210) | EE-IMVC | TPAMI 2020 | - |
| [Adversarial Deep Embedded Clustering: on a better trade-off between Feature Randomness and Feature Drift](https://arxiv.org/pdf/1909.11832v1.pdf) | ADEC | TKDE 2020 | - |
| [Image Clustering via Deep Embedded Dimensionality Reduction and Probability-Based Triplet Loss](https://ieeexplore.ieee.org/document/9062501) | DERC | TIP 2020 | [TensorFlow](https://github.com/DizzyDwarf75/DERC) |
| [Deep Clustering with a Dynamic Autoencoder: From Reconstruction Towards Centroids Construction](https://arxiv.org/pdf/1901.07752v5.pdf) | DynAE | Neural Networks 2020 | [TensorFlow](https://github.com/nairouz/DynAE) |
| [Spectral Clustering via Ensemble Deep Autoencoder Learning (SC-EDAE)](https://www.sciencedirect.com/science/article/pii/S0031320320303253) | SC-EDAE | PR 2020 | - |
| [Optimal Sampling and Clustering in the Stochastic Block Model](https://papers.NeurIPS.cc/paper/9498-optimal-sampling-and-clustering-in-the-stochastic-block-model) | - | NeurIPS 2019 | [Python](https://github.com/fbsqkd/StochasticBlockModel) |
| [Selective Sampling-based Scalable Sparse Subspace Clustering](https://papers.NeurIPS.cc/paper/9408-selective-sampling-based-scalable-sparse-subspace-clustering) | S5C | NeurIPS 2019 | [MATLAB](https://github.com/smatsus/S5C) |
| [GEMSEC: Graph Embedding with Self Clustering](https://arxiv.org/pdf/1802.03997.pdf) | GEMSEC | ASONAM 2019 | [TensorFlow](https://github.com/benedekrozemberczki/GEMSEC) |
| [Video Face Clustering with Unknown Number of Clusters](http://openaccess.thecvf.com/content_ICCV_2019/papers/Tapaswi_Video_Face_Clustering_With_Unknown_Number_of_Clusters_ICCV_2019_paper.pdf) | BCL | ICCV 2019 | [Pytorch](https://github.com/makarandtapaswi/BallClustering_ICCV2019/blob/master/modules.py) |
| [ClusterSLAM: A SLAM Backend for Simultaneous Rigid Body](http://openaccess.thecvf.com/content_ICCV_2019/papers/Huang_ClusterSLAM_A_SLAM_Backend_for_Simultaneous_Rigid_Body_Clustering_and_ICCV_2019_paper.pdf) | ClusterSLAM | ICCV 2019 | - |
| [Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embedding](http://openaccess.thecvf.com/content_ICCV_2019/papers/Yang_Deep_Clustering_by_Gaussian_Mixture_Variational_Autoencoders_With_Graph_Embedding_ICCV_2019_paper.pdf) | DGG | ICCV 2019 | [Pytorch](https://github.com/ngoc-nguyen-0/DGG) |
| [Deep Comprehensive Correlation Mining for Image Clustering](http://openaccess.thecvf.com/content_ICCV_2019/papers/Wu_Deep_Comprehensive_Correlation_Mining_for_Image_Clustering_ICCV_2019_paper.pdf) | DCCM | ICCV 2019 | [Pytorch](https://github.com/Cory-M/DCCM) |
| [Invariant Information Clustering for Unsupervised Image Classification and Segmentation](http://openaccess.thecvf.com/content_ICCV_2019/papers/Ji_Invariant_Information_Clustering_for_Unsupervised_Image_Classification_and_Segmentation_ICCV_2019_paper.pdf) | IIC | ICCV 2019 | [Pytorch](https://github.com/xu-ji/IIC) |
| [Subspace Structure-aware Spectral Clustering for Robust Subspace Clustering](http://openaccess.thecvf.com/content_ICCV_2019/papers/Yamaguchi_Subspace_Structure-Aware_Spectral_Clustering_for_Robust_Subspace_Clustering_ICCV_2019_paper.pdf) | - | ICCV 2019 | - |
| [Is an Affine Constraint Needed for Affine Subspace Clustering?](http://openaccess.thecvf.com/content_ICCV_2019/papers/You_Is_an_Affine_Constraint_Needed_for_Affine_Subspace_Clustering_ICCV_2019_paper.pdf) | - | ICCV 2019 | - |
| [Deep Spectral Clustering using Dual Autoencoder Network](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yang_Deep_Spectral_Clustering_Using_Dual_Autoencoder_Network_CVPR_2019_paper.pdf) | - | ICCV 2019 | [Tensorflow](https://github.com/xdxuyang/Deep-Spectral-Clustering-using-Dual-Autoencoder-Network) |
| [Learning to Discover Novel Visual Categories via Deep Transfer Clustering](http://openaccess.thecvf.com/content_ICCV_2019/papers/Han_Learning_to_Discover_Novel_Visual_Categories_via_Deep_Transfer_Clustering_ICCV_2019_paper.pdf) | DTC | ICCV 2019 | [Pytorch](https://github.com/benjaminirving/DTC-testing/tree/5230618d10575ad28e025792c5470883e3be4f67) |
| [Reciprocal Multi-Layer Subspace Learning for Multi-View Clustering](http://openaccess.thecvf.com/content_ICCV_2019/papers/Li_Reciprocal_Multi-Layer_Subspace_Learning_for_Multi-View_Clustering_ICCV_2019_paper.pdf) | RMSL | ICCV 2019 | - |
| [Adversarial Graph Embedding for Ensemble Clustering](https://www.ijcai.org/proceedings/2019/0494.pdf) | AGAE | IJCAI 2019 | - |
| [Attributed Graph Clustering: A Deep Attentional Embedding Approach](https://arxiv.org/abs/1906.06532) | DAEGC | IJCAI 2019 | - |
| [Neural Collaborative Subspace Clustering](http://proceedings.mlr.press/v97/zhang19g/zhang19g.pdf) | - | ICML 2019 | - |
| [Self-Supervised Convolutional Subspace Clustering Network](https://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_Self-Supervised_Convolutional_Subspace_Clustering_Network_CVPR_2019_paper.pdf) | S^2ConvSCN | CVPR 2019 | - |
| [Balanced Self-Paced Learning for Generative Adversarial Clustering Network](http://openaccess.thecvf.com/content_CVPR_2019/papers/Ghasedi_Balanced_Self-Paced_Learning_for_Generative_Adversarial_Clustering_Network_CVPR_2019_paper.pdf) | ClusterGAN | CVPR 2019 | - |
| [Learning to Cluster Faces on an Affinity Graph](http://personal.ie.cuhk.edu.hk/~ccloy/files/cvpr_2019_cluster.pdf) |  LTC | CVPR 2019 | [Pytorch](https://github.com/yl-1993/learn-to-cluster) |
| [Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering](https://arxiv.org/abs/1803.05206) | LTVAE | ICLR 2019 | [Pytorch](https://github.com/eelxpeng/ltvae-release) |
| [Clustering Meets Implicit Generative Models](https://openreview.net/forum?id=rk4QYDkwz) | - | ICLR 2019 workshop | - |
| [ClusterGAN: Latent Space Clustering in Generative Adversarial Networks](https://arxiv.org/abs/1809.03627) | ClusterGAN | AAAI 2019 | [TensorFlow](https://github.com/sudiptodip15/ClusterGAN) |
| [Adaptive Self-paced Deep Clustering with Data Augmentation](https://ieeexplore.ieee.org/document/8693526) | ASPC-DA | TKDE 2019 | [TensorFlow](https://github.com/XifengGuo/ASPC-DA) |
| [A Hybrid Autoencoder Network for Unsupervised Image Clustering](https://www.mdpi.com/1999-4893/12/6/122/pdf) | - | Algorithms 2019 | - |
| [A Deep Clustering Algorithm based on Gaussian Mixture Model](https://iopscience.iop.org/article/10.1088/1742-6596/1302/3/032012/pdf) | - | JPCS 2019 | - |
| [Deep Clustering with Convolutional Autoencoders](https://xifengguo.github.io/papers/ICONIP17-DCEC.pdf) | DCEC | ICONIP 2018 | [Keras](https://github.com/XifengGuo/DCEC) |
| [Deep Embedded Clustering with Data Augmentation](http://proceedings.mlr.press/v95/guo18b/guo18b.pdf) | DEC-DA | ACML 2018 | [TensorFlow](https://github.com/XifengGuo/DEC-DA) |
| [Deep Clustering for Unsupervised Learning of Visual Features](https://arxiv.org/abs/1807.05520) | DeepCluster | ECCV 2018 | [Pytorch](https://github.com/facebookresearch/deepcluster) |
| [SpectralNet: Spectral Clustering Using Deep Neural Networks](https://openreview.net/pdf?id=HJ_aoCyRZ) | SpectralNet | ICLR 2018 | [TensorFlow](https://github.com/KlugerLab/SpectralNet) |
| [Subspace Clustering using a Low-rank Constrained Autoencoder](https://www.sciencedirect.com/science/article/pii/S0020025517309659) | LRAE | Information Science 2018 | - |
| [Deep Discriminative Latent Space for Clustering](https://arxiv.org/abs/1805.10795) | - |  NeurIPS 2017  | - |
| [Deep Subspace Clustering Networks](http://papers.NeurIPS.cc/paper/6608-deep-subspace-clustering-networks.pdf) | DSC-Nets | NeurIPS 2017 | [TensorFlow](https://github.com/panji1990/Deep-subspace-clustering-networks) |
| [Is Simple Better?: Revisiting Simple Generative Models for Unsupervised Clustering](https://ic.unicamp.br/~adin/downloads/pubs/AriasFigueroa2017a.pdf) | - | NeurIPS 2017 Workshop | [Pytorch](https://github.com/jariasf/clustering-NeurIPS-2017) |
| [Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization](https://arxiv.org/pdf/1704.06327.pdf) |  DEPICT | ICCV 2017 | [Theano](https://github.com/herandy/DEPICT) |
| [Deep Adaptive Image Clustering](http://openaccess.thecvf.com/content_ICCV_2017/papers/Chang_Deep_Adaptive_Image_ICCV_2017_paper.pdf) | DAC | ICCV 2017 | [Keras](https://github.com/vector-1127/DAC) |
| [Improved Deep Embedded Clustering with Local Structure Preservation](https://www.ijcai.org/proceedings/2017/0243.pdf) | IDEC | IJCAI 2017 | [Keras](https://github.com/XifengGuo/IDEC) [Pytorch](https://github.com/dawnranger/IDEC-pytorch) |
| [Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering](https://arxiv.org/pdf/1611.05148.pdf) | VaDE | IJCAI 2017 | [Keras](https://github.com/slim1017/VaDE) |
| [Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering](https://arxiv.org/pdf/1610.04794.pdf) | DCN | ICML 2017 | [Theano](https://github.com/boyangumn/DCN-New) |
| [Learning Discrete Representations via Information Maximizing Self-Augmented Training](https://arxiv.org/pdf/1702.08720.pdf) | IMSAT | ICML 2017 | [Python](https://github.com/weihua916/imsat) |
| [Deep Unsupervised Clustering With Gaussian Mixture Variational AutoEncoders](https://arxiv.org/pdf/1611.02648.pdf) | GMVAE | ICLR 2017 | [Lua](https://github.com/Nat-D/GMVAE) |
| [Cascade Subspace Clustering](https://www.aaai.org/ocs/index.php/AAAI/AAAI17/paper/viewFile/14442/14433) | CSC | AAAI 2017 | - |
| [Unsupervised Multi-Manifold Clustering by Learning Deep Representation](https://pdfs.semanticscholar.org/b852/81d8729038148fd3d8297ea35d632d2e017c.pdf) | DMC | AAAI 2017 Workshop | - |
| [CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data](https://arxiv.org/abs/1705.07091) | - | TMM 2017 | - |
| [Unsupervised Deep Embedding for Clustering Analysis](http://proceedings.mlr.press/v48/xieb16.pdf) | DEC | ICML 2016 | [Caffe](https://github.com/piiswrong/dec) [TensorFlow](https://github.com/danathughes/DeepEmbeddedClustering) |
| [Joint Unsupervised Learning of Deep Representations and Image Clusters](https://arxiv.org/pdf/1604.03628.pdf) | JULE | CVPR 2016 | [Torch](https://github.com/jwyang/JULE.torch) |
| [Deep Embedding Network for Clustering](https://ieeexplore.ieee.org/document/6976982/) | DEN | ICPR 2014 | - |
| [Learning Deep Representations for Graph Clustering](https://www.aaai.org/ocs/index.php/AAAI/AAAI14/paper/viewFile/8527/8571) | - | AAAI 2014 | [Python](https://github.com/quinngroup/deep-representations-clustering) |
| [Auto-encoder Based Data Clustering](http://nlpr-web.ia.ac.cn/english/irds/People/lwang/M-MCG_EN/Publications/2013/CFS2013CIARP.pdf) | ABDC | CIARP 2013 | [Pytorch](https://github.com/KellerJordan/Autoencoder-Clustering) |
| [Discriminative Clustering by Regularized Information Maximization](https://papers.NeurIPS.cc/paper/4154-discriminative-clustering-by-regularized-information-maximization) | RIM | NeurIPS 2010 | - |

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