Stanford Cars
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | Stanford Cars | Accuracy99.5 | 660 | |
| Fine-grained Image Classification | Stanford Cars (test) | Accuracy97.3 | 372 | |
| Image Classification | Stanford Cars (test) | Accuracy96.13 | 320 | |
| Fine-grained Image Classification | Stanford Cars | Accuracy95.7 | 284 | |
| Generalized Category Discovery | Stanford Cars | Accuracy (All)91.1 | 208 | |
| Fine-grained Visual Categorization | Stanford Cars (test) | Accuracy96.3 | 114 | |
| Image Classification | Stanford Cars | Top-1 Accuracy95.22 | 104 | |
| Image Classification | Stanford Cars | Top-1 Accuracy92.9 | 98 | |
| Fine-grained classification | Stanford Cars | Accuracy95 | 74 | |
| Category Discovery | Stanford Cars | Accuracy (All)60.4 | 71 | |
| Selective Prediction | Stanford Cars | Selective Prediction Error5.35 | 60 | |
| Image Classification | Stanford Cars (val) | Accuracy94.5 | 59 | |
| Image Classification | Stanford Cars | Accuracy92.1 | 44 | |
| Fine-grained 5-way classification | Stanford Cars | 1-shot Accuracy92.62 | 40 | |
| Class-Incremental Learning | Stanford Cars (test) | Accuracy (Last)54.86 | 38 | |
| Fine-grained object category discovery | Stanford Cars (test) | Accuracy78 | 38 | |
| Generalized Category Discovery | Stanford Cars (test) | Accuracy (All Classes)63.6 | 33 | |
| Class-Incremental Learning | Stanford Cars CIL, T=10 (test) | Avg Accuracy77.5 | 33 | |
| Image Classification | Stanford Cars few-shot | Score (%)74.6 | 32 | |
| Continual Learning | Stanford Cars | Average Forgetting2.9 | 30 | |
| Image Classification | Stanford Cars | Top-1 Accuracy (Clean)68.91 | 29 | |
| Fine-Grained Image Classification | Stanford Cars | Base Accuracy90 | 27 | |
| Image Classification | Stanford Cars | Top-1 Error Rate3.8 | 26 | |
| Clustering (Color) | Stanford Cars | NMI81.38 | 24 | |
| OOD detection | Stanford Cars | AUROC99.99 | 21 |
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