HyperAI超神经

首页资讯论文教程数据集百科 SOTA LLM 模型天梯 GPU 天梯顶会

中文

HyperAI超神经

Image Clustering On Tiny Imagenet

评估指标

Accuracy

NMI

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	NMI	Paper Title	Repository
DAC	0.066	0.190	Deep Adaptive Image Clustering	-
MMDC	0.119	0.274	Multi-Modal Deep Clustering: Unsupervised Partitioning of Images
GAN	0.041	0.135	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
PRO-DSC	0.698	0.805	Exploring a Principled Framework For Deep Subspace Clustering	-
VAE	0.036	0.113	Auto-Encoding Variational Bayes
SPICE	0.305	0.449	SPICE: Semantic Pseudo-labeling for Image Clustering
ITAE	0.6823	0.8178	Improving Image Clustering with Artifacts Attenuation via Inference-Time Attention Engineering	-
DEC	0.037	0.115	Unsupervised Deep Embedding for Clustering Analysis
CC	0.14	0.34	Contrastive Clustering
C3	0.141	0.335	C3: Cross-instance guided Contrastive Clustering
IMC-SwAV (Best)	0.282	0.526	Information Maximization Clustering via Multi-View Self-Labelling
DCCM	0.108	0.224	Deep Comprehensive Correlation Mining for Image Clustering
JULE	0.033	0.102	Joint Unsupervised Learning of Deep Representations and Image Clusters
IMC-SwAV (Avg+-)	0.279	0.485	Information Maximization Clustering via Multi-View Self-Labelling

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