Image Clustering On Stl 10

Accuracy

Backbone

Results

Performance results of various models on this benchmark

Comparison Table

Model Name	Accuracy	Backbone
improving-unsupervised-image-clustering-with	0.867	ResNet-18
contrastive-clustering	0.85	ResNet34
auto-encoding-variational-bayes	0.282	-
information-maximization-clustering-via-multi	0.853	ResNet-18
deep-comprehensive-correlation-mining-for	0.482	AlexNet
spice-semantic-pseudo-labeling-for-image	0.929	ResNet-34
mice-mixture-of-contrastive-experts-for-1	0.752	ResNet-34
image-clustering-with-external-guidance	0.982	-
let-go-of-your-labels-with-unsupervised-1	0.997	-
contrastive-hierarchical-clustering	0.613	ResNet-50
learning-to-classify-images-without-labels	0.767	ResNet-18
stable-cluster-discrimination-for-deep-1	0.836	ResNet-18
representation-learning-for-clustering-via	0.749	-
multi-modal-deep-clustering-unsupervised	0.694	ResNet18
improving-image-clustering-with-artifacts	0.8276	ViT-B/14
deep-adaptive-image-clustering	0.470	ConvNet
clustering-friendly-representation-learning-1	0.756	ResNet-18
the-balanced-pairwise-affinities-feature	0.943	ResNet-34
twin-contrastive-learning-for-online	0.868	ResNet-34
learning-diverse-and-discriminative	0.491	-
learning-to-classify-images-without-labels	0.809	ResNet-18
Model 22	0.908	ResNet-18
unsupervised-representation-learning-with-1	0.298	-
joint-unsupervised-learning-of-deep	0.277	-
information-maximization-clustering-via-multi	0.831	ResNet-18
unsupervised-deep-embedding-for-clustering	0.359	-
exploring-the-limits-of-deep-image-clustering	0.985	ViT-B
mitigating-embedding-and-class-assignment	0.665	ResNet-18
deep-probability-aggregation-clustering	0.934	ResNet-34