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SOTA
소수 샷 이미지 분류
Few Shot Image Classification On Tiered
Few Shot Image Classification On Tiered
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Accuracy
Paper Title
Repository
TapNet
63.08
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
-
DiffKendall (Meta-Baseline, ResNet-12)
70.76
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation
-
CAML [Laion-2b]
96.8
Context-Aware Meta-Learning
-
HCTransformers
79.67
Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning
-
Adaptive Subspace Network
68.44
Adaptive Subspaces for Few-Shot Learning
LST
77.7
Learning to Self-Train for Semi-Supervised Few-Shot Classification
-
BD-CSPN + ESFR (ResNet-18)
80.13
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification
-
RENet
71.61
Relational Embedding for Few-Shot Classification
-
ASY ResNet12 (transductive)
83.98
EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
-
MTUNet+WRN
62.42
Match Them Up: Visually Explainable Few-shot Image Classification
-
TIM-GD
82.1
Transductive Information Maximization For Few-Shot Learning
-
EASY 3xResNet12 (inductive)
74.71
EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
-
GML (ResNet-12)
69.61
Geometric Mean Improves Loss For Few-Shot Learning
-
ASY ResNet12 (ours)
74.31
EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
-
SImPa
70.82
PAC-Bayes meta-learning with implicit task-specific posteriors
-
Deep Comparison Network
68.83
RelationNet2: Deep Comparison Columns for Few-Shot Learning
-
AM3-TADAM
69.08
Adaptive Cross-Modal Few-Shot Learning
-
Transductive CNAPS
65.9
Enhancing Few-Shot Image Classification with Unlabelled Examples
-
Simple CNAPS + FETI
71.4
Improved Few-Shot Visual Classification
-
BAVARDAGE
85.20
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification
-
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