| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | Oxford Flowers 102 | Accuracy99.56 | 234 | |
| Image Classification | Oxford Flowers-102 (test) | Top-1 Accuracy99.847 | 192 | |
| Image Classification | Oxford-Flowers | Top-1 Accuracy99.7 | 83 | |
| Image Classification | Oxford 102 Flowers | Top-1 Accuracy99.6 | 74 | |
| Image Classification | Oxford Flowers (test) | Accuracy99.65 | 73 | |
| Fine-grained Image Classification | Oxford Flowers | Accuracy97.7 | 49 | |
| Image Classification | Oxford Flowers | Base Accuracy99 | 39 | |
| Image Classification | Oxford 102 Flowers (test) | Mean Per-Class Accuracy99.1 | 34 | |
| Fine-grained classification | Oxford Flowers 102 | Accuracy76.9 | 31 | |
| Fine-grained Image Classification | Oxford Flowers (test) | Top-1 Accuracy99.7 | 24 | |
| Fine-grained Image Classification | Oxford 102 Flowers (test) | Accuracy99.5 | 23 | |
| Concept Erasure | Oxford Flowers (test) | Aer100 | 21 | |
| Image Classification | Oxford Flowers 102 (FLW) | Accuracy70.07 | 21 | |
| Image Generation | Oxford Flowers | FID12.64 | 15 | |
| Few-shot Classification | Oxford Flowers | Accuracy99.48 | 15 | |
| Image Classification | Oxford Flowers 102 | Base Accuracy98.17 | 13 | |
| Base-to-novel generalization | Oxford Flowers | Base Accuracy98.29 | 13 | |
| Image Classification | Oxford Flowers zero-shot | Clean Accuracy75.8 | 11 | |
| Concept Erasure | Oxford Flowers Camellia | Accuracy (Target)100 | 11 | |
| Concept Erasure | Oxford Flowers Alpine Sea Holly | Accuracy (Test)100 | 11 | |
| Image Classification, OOD Detection, and Adversarial Attack Detection | Oxford Flowers low-shot (ID) -> Deep Weeds (OOD) (test) | ID Accuracy (%)100 | 11 | |
| Image Classification | Oxford Flowers-102 (val) | Top-1 Accuracy98.9 | 9 | |
| Image Classification | Oxford Flowers 102 WRN16 (test) | Accuracy88.04 | 8 | |
| Conditional Image Generation | Oxford-Flowers | gFID10.63 | 8 | |
| Image Classification | FLO (Oxford Flowers) (unseen) | Accuracy71.9 | 8 |