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HyperAI超神经

Unsupervised Few Shot Image Classification On 3

评估指标

Accuracy

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	Paper Title	Repository
UniSiam	86.51	Self-Supervision Can Be a Good Few-Shot Learner	-
UBC-FSL	84.3	Shot in the Dark: Few-Shot Learning with No Base-Class Labels	-
ArL	58.56	Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning	-
PL-CFE	64.31	Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-Learning	-
ULDA	56.78	Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation	-
U-MlSo	57.53	Multi-level Second-order Few-shot Learning	-
SAMPTransfer (Conv4)	65.19	Self-Attention Message Passing for Contrastive Few-Shot Learning	-
BECLR	87.86	BECLR: Batch Enhanced Contrastive Few-Shot Learning	-
HMS	75.85	Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks	-
LF2CS	66.59	Unsupervised Few-Shot Image Classification by Learning Features into Clustering Space
PDA-Net	84.20	Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images	-
CPNWCP	62.96	Contrastive Prototypical Network with Wasserstein Confidence Penalty

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Unsupervised Few Shot Image Classification On 3 | SOTA | HyperAI超神经