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SOTA
Few Shot Image Classification
Few Shot Image Classification On Meta Dataset 1
Few Shot Image Classification On Meta Dataset 1
评估指标
Mean Rank
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Mean Rank
Paper Title
Repository
SUR-pnf
4.25
Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification
Transductive CNAPS
3.05
Enhancing Few-Shot Image Classification with Unlabelled Examples
fo-MAML
10.25
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
URT
2.85
A Universal Representation Transformer Layer for Few-Shot Image Classification
SUR
4.2
Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification
Prototypical Networks
8.5
Prototypical Networks for Few-shot Learning
CNAPs
5.95
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes
Matching Networks
10.5
Matching Networks for One Shot Learning
Simple CNAPS
3.45
Improved Few-Shot Visual Classification
k-NN
10.85
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
fo-Proto-MAML
6.65
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Relation Networks
11.8
Learning to Compare: Relation Network for Few-Shot Learning
Finetune
8.7
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
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