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Models that learn to label each image (i.e. cluster the dataset into its ground truth classes) without seeing the ground truth labels.

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

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Datasets

Greatest papers with code

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

19 Nov 2015tensorflow/models

In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications.

CONDITIONAL IMAGE GENERATION IMAGE CLUSTERING UNSUPERVISED REPRESENTATION LEARNING

Auto-Encoding Variational Bayes

20 Dec 2013pytorch/botorch

First, we show that a reparameterization of the variational lower bound yields a lower bound estimator that can be straightforwardly optimized using standard stochastic gradient methods.

IMAGE CLUSTERING VARIATIONAL INFERENCE

Symmetric Nonnegative Matrix Factorization for Graph Clustering

SDM 2012 benedekrozemberczki/karateclub

Unlike NMF, however, SymNMF is based on a similarity measure between data points, and factorizes a symmetric matrix containing pairwise similarity values (not necessarily nonnegative).

GRAPH CLUSTERING IMAGE CLUSTERING SPECTRAL GRAPH CLUSTERING

Self-labelling via simultaneous clustering and representation learning

ICLR 2020 yukimasano/self-label

Combining clustering and representation learning is one of the most promising approaches for unsupervised learning of deep neural networks.

IMAGE CLUSTERING REPRESENTATION LEARNING SELF-SUPERVISED IMAGE CLASSIFICATION SELF-SUPERVISED LEARNING

Joint Unsupervised Learning of Deep Representations and Image Clusters

CVPR 2016 jwyang/joint-unsupervised-learning

In this paper, we propose a recurrent framework for Joint Unsupervised LEarning (JULE) of deep representations and image clusters.

IMAGE CLUSTERING REPRESENTATION LEARNING

FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery

CVPR 2019 kkanshul/finegan

We propose FineGAN, a novel unsupervised GAN framework, which disentangles the background, object shape, and object appearance to hierarchically generate images of fine-grained object categories.

CONDITIONAL IMAGE GENERATION FINE-GRAINED VISUAL CATEGORIZATION IMAGE CLUSTERING

Unsupervised Deep Embedding for Clustering Analysis

19 Nov 2015elieJalbout/Clustering-with-Deep-learning

Clustering is central to many data-driven application domains and has been studied extensively in terms of distance functions and grouping algorithms.

Ranked #3 on Unsupervised Image Classification on SVHN (using extra training data)

IMAGE CLUSTERING UNSUPERVISED IMAGE CLASSIFICATION

Deep Subspace Clustering Networks

NeurIPS 2017 panji1990/Deep-subspace-clustering-networks

We present a novel deep neural network architecture for unsupervised subspace clustering.

IMAGE CLUSTERING

Sparse Subspace Clustering: Algorithm, Theory, and Applications

5 Mar 2012panji1990/Deep-subspace-clustering-networks

In this paper, we propose and study an algorithm, called Sparse Subspace Clustering (SSC), to cluster data points that lie in a union of low-dimensional subspaces.

FACE CLUSTERING MOTION SEGMENTATION