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Unsupervised Image Classification

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)

Papers

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Showing 41–45 of 45 papers

Title	Date	Tasks	Status	Hype
Learning Discrete Representations via Information Maximizing Self-Augmented Training	Feb 28, 2017	ClusteringData Augmentation	CodeCode Available	0
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets	Jun 12, 2016	Generative Adversarial NetworkImage Generation	CodeCode Available	1
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks	Nov 19, 2015	ClusteringGeneral Classification	CodeCode Available	0
Unsupervised Deep Embedding for Clustering Analysis	Nov 19, 2015	ClusteringImage Clustering	CodeCode Available	1
Adversarial Autoencoders	Nov 18, 2015	ClusteringData Visualization	CodeCode Available	1

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