| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | Food101 | Accuracy95.4 | 177 | |
| Image Classification | Food101 (test) | Accuracy96.38 | 97 | |
| Image Classification | Food101 | Base Accuracy91.8 | 69 | |
| Image Classification | Food101 | Robust Accuracy96.11 | 56 | |
| Image-to-image retrieval | Food101 | mAP71 | 55 | |
| Fine-grained Classification | Food101 | Top-1 Acc94.7 | 52 | |
| Class-Incremental Learning | Food101-LT rho=100 (test) | Accuracy36.84 | 48 | |
| Image Classification | Food101 Base-to-new generalization | Accuracy (Base Classes)93.75 | 47 | |
| Category Discovery | Food101 | Accuracy (All)61.2 | 45 | |
| Image Classification | Food101 novel classes | Accuracy0.9205 | 36 | |
| Multimodal Classification | FOOD101 UPMC (train test) | Accuracy94.2 | 36 | |
| Image Classification | Food101 | Top-1 Accuracy96.38 | 33 | |
| Error Detection | Food101 | AuROC99.92 | 29 | |
| OOD Detection | Food101 | AUROC92.63 | 27 | |
| Fine-grained classification | Food101 (base classes) | Accuracy91.71 | 27 | |
| Image Classification | Food101 | Top-1 Accuracy92.33 | 24 | |
| Image Classification | Food101N | Accuracy85.61 | 19 | |
| Image Classification | Food101 | AULC77.9 | 18 | |
| Image Classification | Food101 | Clean Accuracy87.2 | 17 | |
| Long-tailed Class-Incremental Learning | Food101 LT | Accuracy34.7 | 16 | |
| Image Classification | Food101 From Half LT (test) | Accuracy38.9 | 16 | |
| Image Classification | Food101 H (harmonic mean) | Accuracy91.38 | 16 | |
| Image Classification | Food101 Base | Top-1 Accuracy91.63 | 16 | |
| Image Classification | Food101N Imbalance Factor 100, raw noise (test) | Top-1 Accuracy84.1 | 15 | |
| Image Classification | Food101N Imbalance Factor 50, raw noise (test) | Top-1 Accuracy84.6 | 15 |