DRIVE
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Retinal vessel segmentation | DRIVE | Accuracy (AC)95.61 | 73 | |
| Retinal Vessel Segmentation | DRIVE (test) | Accuracy97.9 | 52 | |
| Medical Image Segmentation | DRIVE (test) | Dice Score90.5 | 26 | |
| Vessel Segmentation | DRIVE | Accuracy98.98 | 22 | |
| Segmentation | DRIVE (test) | Soft Dice82.38 | 22 | |
| Driving Reasoning | Drive-Internal (test) | First-Frame Joint Accuracy56.48 | 17 | |
| Retinal Vessel Segmentation | DRIVE S1 (in-domain) | Dice80.46 | 15 | |
| Medical Image Segmentation | DRIVE relabeled | Vessel Score82.8 | 9 | |
| Segmentation | DRIVE | Dice Coefficient81.06 | 8 | |
| Vessel Detection | DRIVE (test) | Sensitivity83.09 | 8 | |
| Segmentation | DRIVE | mIoU65.3 | 7 | |
| Medical Image Segmentation | DRIVE | Dice55.8 | 7 | |
| Fundus Image Restoration | DRIVE Synthetic Set (test) | PSNR (dB)38.64 | 6 | |
| Classification | Drive (test) | Accuracy99 | 6 | |
| Retinal vessel segmentation | DRIVE evaluated on unseen Swin model outputs (test) | DICE0.776 | 6 | |
| Vessel Segmentation | DRIVE (test) | Accuracy95.6 | 5 | |
| Skeleton Extraction | DRIVE Continuous-valued | Beta 0 Error0 | 3 | |
| Skeleton Extraction | DRIVE Binary | Beta 0768.8 | 3 | |
| Autonomous Driving | Drive-Internal | Metric- | 0 |
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