SOTAVerified

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 1–10 of 45 papers

TitleStatusHype
Let Go of Your Labels with Unsupervised TransferCode2
DeepDPM: Deep Clustering With an Unknown Number of ClustersCode2
SCAN: Learning to Classify Images without LabelsCode2
Breaking the Reclustering Barrier in Centroid-based Deep ClusteringCode1
Improving Cross-domain Few-shot Classification with Multilayer PerceptronCode1
Stable Cluster Discrimination for Deep ClusteringCode1
The Pursuit of Human Labeling: A New Perspective on Unsupervised LearningCode1
Capsule Network based Contrastive Learning of Unsupervised Visual RepresentationsCode1
iBOT: Image BERT Pre-Training with Online TokenizerCode1
Self-Supervised Learning by Estimating Twin Class DistributionsCode1
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