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Few Shot Image Classification On Cub 200 5 1

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Paper TitleRepository
PT+MAP+SF+BPA (transductive)95.80The Balanced-Pairwise-Affinities Feature Transform
PT+MAP+SF+SOT (transductive)95.80The Self-Optimal-Transport Feature Transform
CAML [Laion-2b]95.8Context-Aware Meta-Learning
PT+MAP+SF (transductive)95.48Few-Shot Learning by Integrating Spatial and Frequency Representation
PEMnE-BMS*94.78Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning
Illumination Augmentation94.73Sill-Net: Feature Augmentation with Separated Illumination Representation
LST+MAP91.68Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network
PT+MAP91.55%Leveraging the Feature Distribution in Transfer-based Few-Shot Learning
EASY 3xResNet12 (transductive)90.56EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
EASY 4xResNet12 (transductive)90.5EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
BAVARDAGE90.42Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification-
ICI89.58Instance Credibility Inference for Few-Shot Learning
Transfer+SGC88.35%Graph-based Interpolation of Feature Vectors for Accurate Few-Shot Classification
ESPT85.45ESPT: A Self-Supervised Episodic Spatial Pretext Task for Improving Few-Shot Learning
TDM84.36Task Discrepancy Maximization for Fine-grained Few-Shot Classification
BD-CSPN + ESFR (ResNet-18)82.68Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification
TIM-GD82.2%Transductive Information Maximization For Few-Shot Learning
LaplacianShot80.96Laplacian Regularized Few-Shot Learning-
S2M2R80.68Charting the Right Manifold: Manifold Mixup for Few-shot Learning
RENet79.49Relational Embedding for Few-Shot Classification
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