Image Clustering On Stl 10

评估指标

Accuracy

Backbone

评测结果

各个模型在此基准测试上的表现结果

模型名称	Accuracy	Backbone	Paper Title	Repository
RUC	0.867	ResNet-18	Improving Unsupervised Image Clustering With Robust Learning	-
CC	0.85	ResNet34	Contrastive Clustering	-
VAE	0.282	-	Auto-Encoding Variational Bayes	-
IMC-SwAV (Best)	0.853	ResNet-18	Information Maximization Clustering via Multi-View Self-Labelling	-
DCCM	0.482	AlexNet	Deep Comprehensive Correlation Mining for Image Clustering	-
SPICE*	0.929	ResNet-34	SPICE: Semantic Pseudo-labeling for Image Clustering	-
MiCE	0.752	ResNet-34	MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering	-
TAC	0.982	-	Image Clustering with External Guidance	-
TURTLE (CLIP + DINOv2)	0.997	-	Let Go of Your Labels with Unsupervised Transfer	-
CoHiClust	0.613	ResNet-50	Contrastive Hierarchical Clustering	-
SCAN (Avg)	0.767	ResNet-18	SCAN: Learning to Classify Images without Labels	-
SeCu	0.836	ResNet-18	Stable Cluster Discrimination for Deep Clustering	-
ConCURL	0.749	-	Representation Learning for Clustering via Building Consensus	-
MMDC	0.694	ResNet18	Multi-Modal Deep Clustering: Unsupervised Partitioning of Images	-
ITAE	0.8276	ViT-B/14	Improving Image Clustering with Artifacts Attenuation via Inference-Time Attention Engineering	-
DAC	0.470	ConvNet	Deep Adaptive Image Clustering
IDFD	0.756	ResNet-18	Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation	-
SPICE-BPA	0.943	ResNet-34	The Balanced-Pairwise-Affinities Feature Transform	-
TCL	0.868	ResNet-34	Twin Contrastive Learning for Online Clustering	-
MCR2	0.491	-	Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction	-

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