Image Classification on Caltech256 5-way 5-shot (test)
93.31AccuracyAutoAugment
Evaluation results
| Method | Links | |
|---|---|---|
| AutoAugmentModel=ResNet502026.02 | 93.31 | |
| RandAugmentModel=ResNet502026.02 | 92.55 | |
| LearnedModel=ViT-Small2026.02 | 92.33 | |
| Random TreeModel=ResNet502026.02 | 92.22 | |
| LearnedModel=ResNet502026.02 | 91.48 | |
| AutoAugmentModel=MobileNet2026.02 | 91.41 | |
| AutoAugmentModel=ViT-Small2026.02 | 90.7 | |
| RandAugmentModel=ViT-Small2026.02 | 90.32 | |
| LearnedModel=MobileNet2026.02 | 90.05 | |
| RandAugmentModel=MobileNet2026.02 | 89.51 | |
| Naive BaselineModel=MobileNet2026.02 | 88.8 | |
| Naive BaselineModel=ResNet502026.02 | 88.15 | |
| Naive BaselineModel=ViT-Small2026.02 | 85.75 |