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HyperAI超神経
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プラットフォーム
ホーム
SOTA
無教師少ショット画像分類
Unsupervised Few Shot Image Classification On
Unsupervised Few Shot Image Classification On
評価指標
Accuracy
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
Accuracy
Paper Title
BECLR
80.57
BECLR: Batch Enhanced Contrastive Few-Shot Learning
Meta-DM+UniSiam
66.68
Meta-DM: Applications of Diffusion Models on Few-Shot Learning
UniSiam
65.55
Self-Supervision Can Be a Good Few-Shot Learner
PDA-Net
63.84
Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images
SAMPTransfer (Conv4)
61.02
Self-Attention Message Passing for Contrastive Few-Shot Learning
Deep Laplacian Eigenmaps
59.47
Unsupervised Few-shot Learning via Deep Laplacian Eigenmaps
TrainProto
58.92
Trainable Class Prototypes for Few-Shot Learning
HMS
58.20
Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks
UBC-FSL
57.1
Shot in the Dark: Few-Shot Learning with No Base-Class Labels
CSSL
54.17
Few-Shot Image Classification via Contrastive Self-Supervised Learning
CPNWCP
53.56
Contrastive Prototypical Network with Wasserstein Confidence Penalty
LF2CS
53.14
Unsupervised Few-Shot Image Classification by Learning Features into Clustering Space
PL-CFE
49.13
Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-Learning
C^3LR
47.92
Self-Supervised Class-Cognizant Few-Shot Classification
PsCo
46.70
Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning
AmdimNet
46.13
Self-Supervised Learning For Few-Shot Image Classification
ProtoTransfer
45.67
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification
CMVAE
44.27
CMVAE: Causal Meta VAE for Unsupervised Meta-Learning
Meta-SVEBM
43.38
Unsupervised Meta-Learning via Latent Space Energy-based Model of Symbol Vector Coupling
Meta-GMVAE
42.82
Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning
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Unsupervised Few Shot Image Classification On | SOTA | HyperAI超神経