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Few Shot Image Classification
Few Shot Image Classification On Mini 12
Few Shot Image Classification On Mini 12
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
Paper Title
Repository
Relation Networks
34.9
Learning to Compare: Relation Network for Few-Shot Learning
Transductive CNAPS + FETI
68.5
Enhancing Few-Shot Image Classification with Unlabelled Examples
Reptile
31.1
On First-Order Meta-Learning Algorithms
Prototypical Networks
32.9
Prototypical Networks for Few-shot Learning
TPN (Higher Shot)
38.4
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Simple CNAPS
37.1
Improved Few-Shot Visual Classification
Reptile+BN
32.0
On First-Order Meta-Learning Algorithms
MAML
31.3
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Simple CNAPS + FETI
63.5
Improved Few-Shot Visual Classification
Transductive CNAPS
42.8
Enhancing Few-Shot Image Classification with Unlabelled Examples
TIM-GD
56.1
Transductive Information Maximization For Few-Shot Learning
Label Propagation
35.2
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Prototypical Networks (Higher Way)
34.6
Prototypical Networks for Few-shot Learning
MAML + Transduction
31.8
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
0 of 14 row(s) selected.
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