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Few Shot Image Classification On Tiered 1

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Model Name
Accuracy
Paper TitleRepository
SKD86.66Self-supervised Knowledge Distillation for Few-shot Learning
Invariance-Equivariance87.08Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
HyperTransformer73.9%HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning
MetaFun-Kernel83.28MetaFun: Meta-Learning with Iterative Functional Updates
Transductive CNAPS81.8Enhancing Few-Shot Image Classification with Unlabelled Examples
BD-CSPN + ESFR (WRN)87.61Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification
EASY 3xResNet12 (inductive)88.33EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
EASY 3xResNet12 (transductive)89.76EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
ICI89.00Instance Credibility Inference for Few-Shot Learning
GML (ResNet-12)84.04Geometric Mean Improves Loss For Few-Shot Learning-
CAML [Laion-2b]98.8Context-Aware Meta-Learning-
AM3-TADAM82.58Adaptive Cross-Modal Few-Shot Learning
pseudo-shots86.82Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks
TIM-GD89.8Transductive Information Maximization For Few-Shot Learning
MTUNet+ResNet-1877.82Match Them Up: Visually Explainable Few-shot Image Classification
BAVARDAGE90.41Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification-
LST85.2Learning to Self-Train for Semi-Supervised Few-Shot Classification
UniSiam86.51Self-Supervision Can Be a Good Few-Shot Learner
MetaQDA89.56Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition
DiffKendall (Meta-Baseline, ResNet-12)85.31DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation
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