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SOTA
Unsupervised Few Shot Image Classification
Unsupervised Few Shot Image Classification On 2
Unsupervised Few Shot Image Classification On 2
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Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Accuracy
Paper Title
Repository
BECLR
81.69
BECLR: Batch Enhanced Contrastive Few-Shot Learning
UniSiam
69.60
Self-Supervision Can Be a Good Few-Shot Learner
LF2CS
53.16
Unsupervised Few-Shot Image Classification by Learning Features into Clustering Space
UBC-FSL
68.0
Shot in the Dark: Few-Shot Learning with No Base-Class Labels
-
HMS
58.42
Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks
ULDA
41.77
Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation
SAMPTransfer (Conv4)
49.10
Self-Attention Message Passing for Contrastive Few-Shot Learning
PL-CFE
49.51
Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-Learning
ArL
43.68
Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning
PDA-Net
69.01
Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images
-
U-MlSo
43.01
Multi-level Second-order Few-shot Learning
CPNWCP
45.00
Contrastive Prototypical Network with Wasserstein Confidence Penalty
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