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Few Shot Image Classification On Mini 12

Metrics

Accuracy

Results

Performance results of various models on this benchmark

		Paper Title	Repository
Transductive CNAPS + FETI	68.5	Enhancing Few-Shot Image Classification with Unlabelled Examples
Simple CNAPS + FETI	63.5	Improved Few-Shot Visual Classification
TIM-GD	56.1	Transductive Information Maximization For Few-Shot Learning
Transductive CNAPS	42.8	Enhancing Few-Shot Image Classification with Unlabelled Examples
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
Label Propagation	35.2	Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Relation Networks	34.9	Learning to Compare: Relation Network for Few-Shot Learning
Prototypical Networks (Higher Way)	34.6	Prototypical Networks for Few-shot Learning
Prototypical Networks	32.9	Prototypical Networks for Few-shot Learning
Reptile+BN	32.0	On First-Order Meta-Learning Algorithms
MAML + Transduction	31.8	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
MAML	31.3	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Reptile	31.1	On First-Order Meta-Learning Algorithms

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Few Shot Image Classification On Mini 12 | SOTA | HyperAI