| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | Caltech101 | Accuracy96.92 | 228 | |
| Image Classification | Caltech-101 | Accuracy98.9 | 208 | |
| Image Classification | Caltech (test) | Accuracy94.5 | 165 | |
| Image Classification | Caltech101 (test) | Accuracy99.12 | 159 | |
| Image Classification | Caltech-101 | Top-1 Accuracy98.6 | 152 | |
| Image Classification | Caltech101 | Base Accuracy99.1 | 148 | |
| Image Classification | Caltech101 | Base Accuracy98.37 | 129 | |
| Image Classification | Caltech | Accuracy97.2 | 101 | |
| Image Classification | Caltech-256 (test) | Top-1 Acc87 | 74 | |
| Image Classification | Caltech256 | Accuracy (Clean)88.84 | 69 | |
| Base-to-New Generalization | Caltech101 | Base Score99 | 58 | |
| Object Recognition | N-Caltech101 | Accuracy94.56 | 51 | |
| Object Classification | N-Caltech101 (test) | Accuracy90.2 | 51 | |
| Image Classification | Caltech-256 | Accuracy97.33 | 47 | |
| Clustering | Caltech 7-5V | ACC90.4 | 40 | |
| Fine-grained classification | Caltech101 | Accuracy95.9 | 39 | |
| Pedestrian Detection | Caltech (test) | MR9.6 | 36 | |
| Partial-label image classification | Caltech (test) | Testing Accuracy87 | 34 | |
| Image Classification | Caltech-256 | Robust Accuracy60.83 | 34 | |
| Classification | Caltech101 | Accuracy97.6 | 34 | |
| Classification | Caltech101 (test) | Accuracy93.79 | 33 | |
| Object Recognition | Caltech101 | Accuracy39.2 | 31 | |
| Semantic Correspondence | Caltech-101 | LT-ACC88 | 31 | |
| Image-to-image retrieval | Caltech | mAP93 | 30 | |
| Image Classification | Caltech-101 | Robust Accuracy72.16 | 29 |