Few-Shot Image Classification on OMNIGLOT - 1-Shot, 5-way

Metric: Accuracy (higher is better)

LeaderboardDataset

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Results

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#	Model↕	Accuracy▼	Extra Data	Paper	Date↕	Code
1	MC2+	99.97	No	Meta-Curvature	2019-02-09	Code
2	Relation Net	99.6	No	Learning to Compare: Relation Network for Few-Sh...	2017-11-16	Code
3	MT-net	99.5	No	Gradient-Based Meta-Learning with Learned Layerw...	2018-01-17	Code
4	iMAML, Hessian-Free	99.5	No	Meta-Learning with Implicit Gradients	2019-09-10	Code
5	MAML++	99.47	No	How to train your MAML	2018-10-22	Code
6	Hyperbolic ProtoNet	99	No	Hyperbolic Image Embeddings	2019-04-03	Code
7	Prototypical Networks	98.8	No	Prototypical Networks for Few-shot Learning	2017-03-15	Code
8	MAML	98.7	No	Model-Agnostic Meta-Learning for Fast Adaptation...	2017-03-09	Code
9	VAMPIRE	98.43	No	Uncertainty in Model-Agnostic Meta-Learning usin...	2019-07-27	Code
10	adaCNN (DF)	98.42	No	Rapid Adaptation with Conditionally Shifted Neur...	2017-12-28	-
11	ConvNet with Memory Module	98.4	No	Learning to Remember Rare Events	2017-03-09	Code
12	Matching Nets	98.1	No	Matching Networks for One Shot Learning	2016-06-13	Code
13	Neural Statistician	98.1	No	Towards a Neural Statistician	2016-06-07	Code
14	APL	97.9	No	Adaptive Posterior Learning: few-shot learning w...	2019-02-07	Code
15	Reptile + Transduction	97.68	No	On First-Order Meta-Learning Algorithms	2018-03-08	Code