Few Shot Image Classification On Mini 5
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy |
|---|---|
| matching-networks-for-one-shot-learning | 45.59 |
| leveraging-the-feature-distribution-in | 62.49 |
| deep-kernel-transfer-in-gaussian-processes | 40.22 |
| model-agnostic-meta-learning-for-fast | 40.15 |
| a-closer-look-at-few-shot-classification-1 | 33.04 |
| squeezing-backbone-feature-distributions-to | 63.90 |
| hypershot-few-shot-learning-by-kernel | 40.03 |
| learning-embedding-adaptation-for-few-shot | 39.00 |
| few-shot-learning-as-domain-adaptation | 49.44 |
| transductive-decoupled-variational-inference | 84.61 |
| learning-to-compare-relation-network-for-few | 42.91 |
| prototypical-networks-for-few-shot-learning | 45.31 |