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 11–20 of 45 papers

TitleStatusHype
Unsupervised Visual Representation Learning by Online Constrained K-MeansCode1
Self-Supervised Classification NetworkCode1
Improving Unsupervised Image Clustering With Robust LearningCode1
Improving Self-Organizing Maps with Unsupervised Feature ExtractionCode1
Self-Supervised Learning for Large-Scale Unsupervised Image ClusteringCode1
Unsupervised Feature Learning by Cross-Level Instance-Group DiscriminationCode1
Mitigating Embedding and Class Assignment Mismatch in Unsupervised Image ClassificationCode1
Deep Transformation-Invariant ClusteringCode1
Invariant Information Clustering for Unsupervised Image Classification and SegmentationCode1
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial NetsCode1
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