Few Shot Image Classification On Stanford 2
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| MML(KL) | 72.43 | Multi-level Metric Learning for Few-shot Image Recognition | - |
| GNN++ | 55.85 | Few-Shot Learning with Graph Neural Networks | |
| Matching Nets FCE++ | 34.80 | Matching Networks for One Shot Learning | |
| Prototypical Nets++ | 40.90 | Prototypical Networks for Few-shot Learning | |
| MATANet | 73.15 | Multi-scale Adaptive Task Attention Network for Few-Shot Learning | - |
| DN4-DA (k=1) | 61.51 | Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning |
0 of 6 row(s) selected.