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Unüberwachte Few-Shot Bildklassifikation
Unsupervised Few Shot Image Classification On 1
Unsupervised Few Shot Image Classification On 1
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Accuracy
Paper Title
BECLR
87.82
BECLR: Batch Enhanced Contrastive Few-Shot Learning
Meta-DM+UniSiam
85.29
Meta-DM: Applications of Diffusion Models on Few-Shot Learning
UniSiam
83.40
Self-Supervision Can Be a Good Few-Shot Learner
PDA-Net
83.11
Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images
Deep Laplacian Eigenmaps
78.79
Unsupervised Few-shot Learning via Deep Laplacian Eigenmaps
UBC-FSL
77.2
Shot in the Dark: Few-Shot Learning with No Base-Class Labels
HMS
75.77
Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks
TrainProto
73.94
Trainable Class Prototypes for Few-Shot Learning
CPNWCP
73.21
Contrastive Prototypical Network with Wasserstein Confidence Penalty
SAMPTransfer (Conv4)
72.52
Self-Attention Message Passing for Contrastive Few-Shot Learning
AmdimNet
70.14
Self-Supervised Learning For Few-Shot Image Classification
CSSL
68.91
Few-Shot Image Classification via Contrastive Self-Supervised Learning
LF2CS
67.36
Unsupervised Few-Shot Image Classification by Learning Features into Clustering Space
C^3LR
64.81
Self-Supervised Class-Cognizant Few-Shot Classification
PsCo
63.26
Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning
ProtoTransfer
62.99
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification
PL-CFE
62.91
Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-Learning
CMVAE
58.95
CMVAE: Causal Meta VAE for Unsupervised Meta-Learning
Meta-SVEBM
58.03
Unsupervised Meta-Learning via Latent Space Energy-based Model of Symbol Vector Coupling
ArL
57.01
Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning
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Unsupervised Few Shot Image Classification On 1 | SOTA | HyperAI