Few Shot Image Classification On Cifar Fs 5 1

المقاييس

Accuracy

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	Accuracy	Paper Title	Repository
EASY 2xResNet12 1/√2 (transductive)	90.2	EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
PT+MAP+SF+SOT (transductive)	92.83	The Self-Optimal-Transport Feature Transform
Adaptive Subspace Network	87.3	Adaptive Subspaces for Few-Shot Learning
BAVARDAGE	90.63	Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification	-
Multi-Task Learning	84.1	Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation
RCN - Conv4-64	77.63	Region Comparison Network for Interpretable Few-shot Image Classification
MTUNet+ResNet-18	80.16	Match Them Up: Visually Explainable Few-shot Image Classification
P>M>F (P=DINO-ViT-base, M=ProtoNet)	92.2	Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference
HCTransformers	90.50	Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning
MetaQDA	88.79	Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition
Invariance-Equivariance	89.74	Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
FewTURE	88.90	Rethinking Generalization in Few-Shot Classification
CAML [Laion-2b]	93.5	Context-Aware Meta-Learning	-
MetaOptNet-SVM-trainval	85	Meta-Learning with Differentiable Convex Optimization
EASY 3xResNet12 (transductive)	90.47	EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
ICI	84.32	Instance Credibility Inference for Few-Shot Learning
LST+MAP	90.73	Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network
EASY 3xResNet12 (inductive)	89.0	EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
MTUNet+WRN	82.93	Match Them Up: Visually Explainable Few-shot Image Classification
S2M2R	87.47	Charting the Right Manifold: Manifold Mixup for Few-shot Learning

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