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Unsupervised Image Classification On Stl 10

Metriken

Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	Accuracy	Paper Title	Repository
HUME	90.8	-	-
SCAN	80.90	SCAN: Learning to Classify Images without Labels	-
IIC	61.00	Invariant Information Clustering for Unsupervised Image Classification and Segmentation	-
MV-MR	89.67	MV-MR: multi-views and multi-representations for self-supervised learning and knowledge distillation	-
IPCL (ResNet18)	-	IPCL: Iterative Pseudo-Supervised Contrastive Learning to Improve Self-Supervised Feature Representation
ScatSimCLR	85.11	ScatSimCLR: self-supervised contrastive learning with pretext task regularization for small-scale datasets	-
TSUC	66.50	Mitigating Embedding and Class Assignment Mismatch in Unsupervised Image Classification
TURTLE (CLIP + DINOv2)	99.7	Let Go of Your Labels with Unsupervised Transfer	-
RUC	86.7	Improving Unsupervised Image Clustering With Robust Learning	-

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Unsupervised Image Classification On Stl 10 | SOTA | HyperAI