Cross-domain Few-shot Character Recognition on Omniglot to EMNIST (novel classes)
88.94AccuracyRelationNet
Evaluation Results
| Method | Links | |
|---|---|---|
| RelationNetN-shot=5-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way2019.04 | 88.94 | |
| MAMLN-shot=5-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way2019.04 | 88.24 | |
| MatchingNetN-shot=5-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way2019.04 | 87.6 | |
| Baseline++N-shot=5-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way, Training Epochs=52019.04 | 87.31 | |
| ProtoNetN-shot=5-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way2019.04 | 87.04 | |
| BaselineN-shot=5-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way, Training Epochs=52019.04 | 86 | |
| RelationNetN-shot=1-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way2019.04 | 75.55 | |
| MatchingNetN-shot=1-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way2019.04 | 72.71 | |
| MAMLN-shot=1-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way2019.04 | 72.04 | |
| ProtoNetN-shot=1-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way2019.04 | 70.43 | |
| Baseline++N-shot=1-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way, Training Epochs=52019.04 | 64.74 | |
| BaselineN-shot=1-shot, Backbone=Conv-4, Data Augmentation=None, N-way=5-way, Training Epochs=52019.04 | 63.94 |