Anchor3DLane† (iterative regression) | 57.2 | 52.5 | 53.7 | 45.4 | 51.2 | 47.8 | 46.7 | Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane Detection | |
PVALane (Swin-B) | 67.7 | 64.0 | 63.4 | 53.6 | 60.8 | 58.6 | 56.1 | PVALane: Prior-Guided 3D Lane Detection with View-Agnostic Feature Alignment | - |
PersFormer (version 1.2) | 58.4 | 51.8 | 52.9 | 42.1 | 50.9 | 47.4 | 47.5 | PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmark | |
PETRv2-V∗ (VoVNetV2 with 400 anchor points) | - | - | 61.2 | - | - | - | - | PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images | |
3D-LaneNet | 46.5 | 47.5 | 44.1 | 32.1 | 41.7 | 41.5 | 40.8 | 3D-LaneNet: End-to-End 3D Multiple Lane Detection | |
PVALane (ResNet-50) | 67.3 | 62.0 | 62.7 | 53.4 | 60.0 | 57.2 | 54.1 | PVALane: Prior-Guided 3D Lane Detection with View-Agnostic Feature Alignment | - |
Anchor3DLane (ResNet-18) | 56.2 | 51.9 | 53.1 | 44.2 | 50.5 | 47.2 | 45.5 | Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane Detection | |
LaneCPP | 64.4 | 56.7 | 60.3 | 52.0 | 58.7 | 54.9 | 53.6 | LaneCPP: Continuous 3D Lane Detection using Physical Priors | - |
M^2-3DLaneNet (Camera + Lidar) | 60.7 | 56.2 | 55.5 | 43.8 | 51.4 | 51.6 | 53.4 | M$^2$-3DLaneNet: Exploring Multi-Modal 3D Lane Detection | - |
PVALane (ResNet-18) | 65.7 | 59.5 | 61.2 | 52.2 | 58.7 | 56.5 | 52.6 | PVALane: Prior-Guided 3D Lane Detection with View-Agnostic Feature Alignment | - |
BEV-LaneDet | 63.1 | 53.4 | 58.4 | 50.3 | 53.7 | 53.4 | 48.7 | BEV-LaneDet: a Simple and Effective 3D Lane Detection Baseline | - |
PersFormer (version 1.1) | 58.7 | 54.0 | 50.5 | 41.6 | 53.1 | 50.0 | 45.6 | PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmark | |
Anchor3DLane-T† (multi-frame + iterative regression) | 58.0 | 52.7 | 54.3 | 45.8 | 51.7 | 48.7 | 47.2 | Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane Detection | |