Lane Detection On Llamas
Métriques
F1
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
Nom du modèle | 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 |