Data Augmentation On Imagenet
Metrics
Accuracy (%)
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy (%) |
|---|---|
| mixpro-data-augmentation-with-maskmix-and | 81.3 |
| tailoring-self-supervision-for-supervised | 77.71 |
| mixpro-data-augmentation-with-maskmix-and | 73.8 |
| uniformaugment-a-search-free-probabilistic | 77.63 |
| deep-autoaugment-1 | 81.32 |
| uniformaugment-a-search-free-probabilistic | 80.4 |
| mixpro-data-augmentation-with-maskmix-and | 82.9 |
| randaugment-practical-data-augmentation-with | 77.6 |
| autoaugment-learning-augmentation-policies | 80.0 |
| deep-autoaugment-1 | 78.30 |
| autoaugment-learning-augmentation-policies | 77.6 |
| faster-autoaugment-learning-augmentation | 76.5 |
| fast-autoaugment | 77.6 |
| fast-autoaugment | 80.6 |
| trivialaugment-tuning-free-yet-state-of-the | 78.07 |
| tailoring-self-supervision-for-supervised | 77.72 |
| dada-differentiable-automatic-data | 77.5 |