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DRIVE

Benchmarks

Task NameDataset NameSOTA ResultTrend
Retinal vessel segmentationDRIVE
Accuracy (AC)95.61
93
Retinal Vessel SegmentationDRIVE (test)
Accuracy97.9
52
Medical Image SegmentationDRIVE
Dice81.63
30
Medical Image SegmentationDRIVE (test)
Dice Score90.5
26
Vessel SegmentationDRIVE
Accuracy98.98
22
SegmentationDRIVE (test)
Soft Dice82.38
22
Driving ReasoningDrive-Internal (test)
First-Frame Joint Accuracy56.48
17
SegmentationDRIVE
mIoU72.8
16
Retinal Vessel SegmentationDRIVE S1 (in-domain)
Dice80.46
15
Medical Image SegmentationDRIVE relabeled
Vessel Score82.8
9
Image SegmentationDRIVE (test)
Dice82.74
8
SegmentationDRIVE
Dice Coefficient81.06
8
Vessel SegmentationDRIVE (test)
mIoU77.44
8
Vessel DetectionDRIVE (test)
Sensitivity83.09
8
Fundus Image RestorationDRIVE Synthetic Set (test)
PSNR (dB)38.64
6
ClassificationDrive (test)
Accuracy99
6
Retinal vessel segmentationDRIVE evaluated on unseen Swin model outputs (test)
DICE0.776
6
Skeleton ExtractionDRIVE Continuous-valued
Beta 0 Error0
3
Skeleton ExtractionDRIVE Binary
Beta 0768.8
3
Autonomous DrivingDrive-Internal
Metric-
0
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