STL-10
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | STL-10 (test) | Accuracy99.71 | 357 | |
| Clustering | STL-10 (test) | Accuracy99.2 | 152 | |
| Generative Image Synthesis | STL-10 SNGAN | FID29.7 | 62 | |
| Image Classification | STL-10 | Top-1 Error5.63 | 36 | |
| Image Classification | STL-10 Clean (test) | Error Rate4.15 | 33 | |
| Clustering | STL-10 | ACC99.8 | 28 | |
| Image Classification | STL-10 USB (test) | Error Rate5.65 | 25 | |
| Image Classification | STL-10 OOD | Accuracy98.6 | 24 | |
| Similarity Confidence | STL-10 | Accuracy74.32 | 22 | |
| Image Classification | STL-10 pre-trained on CIFAR-10 (test) | Balanced Accuracy85.29 | 22 | |
| Image Classification | STL-10 250 labels | Error Rate1.4 | 17 | |
| Positive-Unlabeled Learning | STL-10 (test) | Accuracy99.39 | 14 | |
| Image Classification | STL-10 USB (40 labels) | Error Rate11.09 | 14 | |
| Partial Label Learning | STL-10 | Accuracy86.46 | 12 | |
| Image Classification | STL-10 pre-trained on CIFAR-100 (test) | Average Accuracy31.42 | 12 | |
| Image Classification | STL-10 (test) | Accuracy (Benign)52.14 | 11 | |
| Image Classification | STL-10 40 labels (test) | Top-1 Accuracy85.09 | 10 | |
| Image Reconstruction | STL-10 (test) | PSNR25.8 | 9 | |
| Image Generation | STL-10 low-resolution (test) | FID15.17 | 7 | |
| Unconditional Image Generation | STL-10 (unlabeled) | Inception Score9.53 | 7 | |
| Image Classification | STL-10 standard (test) | Test Error (%)19.25 | 7 | |
| Unconditional Image Generation | STL-10 (train and unlabeled) | Inception Score9.34 | 6 | |
| Image Classification | STL-10 | Adversarial Accuracy83.88 | 5 | |
| Image Generation | STL-10 64 x 64 | FID11.7 | 5 | |
| Cluster number prediction | STL-10 | NC20 | 4 |
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