Cars
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Classification | Cars | Accuracy96.4 | 314 | |
| Image Retrieval | CARS196 (test) | Recall@189.3 | 134 | |
| Image Retrieval | Cars-196 | Recall@194.7 | 98 | |
| Image Classification | Cars (test) | Accuracy96.868 | 57 | |
| Deep Metric Learning | CARS196 (test) | R@189.6 | 56 | |
| Image Retrieval | CARS 196 (test) | Recall@191.5 | 56 | |
| Image Retrieval | CARS196 | Recall@188 | 56 | |
| Deep Metric Learning | CARS196 | Recall@197.4 | 50 | |
| Image Retrieval | Cars | R@198.2 | 44 | |
| Image Retrieval | CARS noise-free (test) | Precision@180.06 | 39 | |
| Image Classification | CARS196 (test) | Accuracy91.5 | 38 | |
| Model Selection | Cars | Weighted Kendall's Tau0.785 | 36 | |
| Few-shot classification | Cars | Accuracy75.15 | 30 | |
| Few-Shot Classification | Cars (test) | Accuracy97.6 | 28 | |
| Few-shot Image Classification | mini-Cars (test) | Accuracy58.09 | 28 | |
| 5-way Few-shot Classification | Cars | Accuracy99.74 | 27 | |
| Image Retrieval | CARS | Precision@177.6 | 26 | |
| Fine-grained Image Classification | Cars 1.0 (val) | Accuracy94.6 | 23 | |
| Class-incremental learning | Cars-196 | Last Accuracy86.79 | 22 | |
| Fine-grained Classification | Cars | Accuracy86.7 | 21 | |
| Clustering | CARS 196 (test) | NMI76.4 | 21 | |
| Fine-grained Image Classification | Cars | Top-1 Acc77.45 | 20 | |
| Fine-grained classification | Cars | Clean Accuracy67.7 | 18 | |
| Image Classification | Cars unlearnable version (test) | Accuracy83.74 | 18 | |
| Image Retrieval | Cars-196 cropped (test) | Recall@193 | 17 |
Showing 25 of 65 rows