Lane Detection On Llamas
Metrics
F1
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | F1 |
|---|---|
| laneaf-robust-multi-lane-detection-with | 0.9601 |
| fenet-focusing-enhanced-network-for-lane | - |
| keep-your-eyes-on-the-lane-attention-guided | 0.9346 |
| rethinking-efficient-lane-detection-via-curve | 0.9552 |
| polylanenet-lane-estimation-via-deep | 0.8840 |
| keep-your-eyes-on-the-lane-attention-guided | 0.9374 |
| clrnet-cross-layer-refinement-network-for | 0.9612 |
| keep-your-eyes-on-the-lane-attention-guided | 0.9354 |
| rethinking-efficient-lane-detection-via-curve | 0.9611 |
| clrnet-cross-layer-refinement-network-for | 0.9600 |