Lane Detection On Llamas
评估指标
F1
评测结果
各个模型在此基准测试上的表现结果
模型名称 | F1 | Paper Title | Repository |
|---|---|---|---|
| LaneAF | 0.9601 | LaneAF: Robust Multi-Lane Detection with Affinity Fields | |
| FENetV2 | - | FENet: Focusing Enhanced Network for Lane Detection | |
| LaneATT (ResNet-18) | 0.9346 | Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection | |
| BézierLaneNet (ResNet-18) | 0.9552 | Rethinking Efficient Lane Detection via Curve Modeling | |
| PolyLaneNet | 0.8840 | PolyLaneNet: Lane Estimation via Deep Polynomial Regression | |
| LaneATT (ResNet-34) | 0.9374 | Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection | |
| CLRNet (DLA-34) | 0.9612 | CLRNet: Cross Layer Refinement Network for Lane Detection | |
| LaneATT (ResNet-122) | 0.9354 | Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection | |
| BézierLaneNet (ResNet-34) | 0.9611 | Rethinking Efficient Lane Detection via Curve Modeling | |
| CLRNet (ResNet-18) | 0.9600 | CLRNet: Cross Layer Refinement Network for Lane Detection |
0 of 10 row(s) selected.