Here are the results from all few shot learning results for Omniglot and Mini-Imagenet.
Omniglot Dataset
| 5-Way 1-Shot | 5-Way 5-Shot | 20-Way 1-Shot | 20-Way 5-Shot | |
|---|---|---|---|---|
| Matching Network | 98.1 | 98.9 | 93.8 | 98.5 |
| Prototypical Network | 98.8 | 99.7 | 96.0 | 98.9 |
| Model Agnostic Meta-Learning | 98.7 | 99.9 | 95.8 | 98.6 |
| Neural Statistician | 98.1 | 99.7 | 96.0 | 98.9 |
| Siamese Network | 97.3 | 94.9 | ||
| Memory Augmented Neural Network | 82.8 | 94.9 | ||
| Learning to Remember Rare-Events | 98.4 | 99.6 | 95.0 | 98.6 |
| Relation Network | 99.6 | 99.8 | 97.6 | 99.1 |
| MetaNet | 99.0 | 97.0 | ||
| Gaussian Prototypical Network | 99.07 | 99.73 | 96.94 | 99.29 |
| SNAIL | 99.07 | 99.78 | 97.64 | 99.36 |
miniImageNet Dataset
| 5-Way 1-Shot | 5-Way 5-Shot | |
|---|---|---|
| Matching Network | 43.6 | 55.3 |
| Prototypical Network | 49.42 | 68.20 |
| Model Agnostic Meta-Learning | 48.7 | 63.1 |
| Relation Network | 50.44 | 65.32 |
| MetaNet | 49.21 | |
| SNAIL | 55.71 | 68.88 |