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Few-Shot Image Classification
Few Shot Image Classification On Meta Dataset 1
Few Shot Image Classification On Meta Dataset 1
Metrics
Mean Rank
Results
Performance results of various models on this benchmark
Columns
Model Name
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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