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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
Inferencing Based on Unsupervised Learning of Disentangled Representations	Mar 7, 2018	DescriptiveRepresentation Learning	CodeCode Available	0
Learning Latent Representations in Neural Networks for Clustering through Pseudo Supervision and Graph-based Activity Regularization	Feb 8, 2018	ClusteringUnsupervised Image Classification	—Unverified	0
PixelGAN Autoencoders	Jun 2, 2017	DecoderGenerative Adversarial Network	—Unverified	0
Learning Discrete Representations via Information Maximizing Self-Augmented Training	Feb 28, 2017	ClusteringData Augmentation	CodeCode Available	0
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks	Nov 19, 2015	ClusteringGeneral Classification	CodeCode Available	0

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