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3D Lane Detection

The goal of 3D Lane Detection is to perceive lanes that provide guidance for autonomous vehicles. A lane can be represented as a visible laneline or a conceptual centerline. Furthermore, a lane obtains extra attributes from the understanding of the surrounding environment.

( Image credit: OpenLane-V2 )

Papers

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Showing 1–10 of 54 papers

TitleStatusHype
Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation ModelsCode3
DB3D-L: Depth-aware BEV Feature Transformation for Accurate 3D Lane Detection—0
GLane3D : Detecting Lanes with Graph of 3D Keypoints—0
Rethinking Lanes and Points in Complex Scenarios for Monocular 3D Lane Detection—0
GLane3D: Detecting Lanes with Graph of 3D Keypoints—0
TopoBDA: Towards Bezier Deformable Attention for Road Topology Understanding—0
Anchor3DLane++: 3D Lane Detection via Sample-Adaptive Sparse 3D Anchor RegressionCode2
Monocular Lane Detection Based on Deep Learning: A SurveyCode2
TopoMaskV2: Enhanced Instance-Mask-Based Formulation for the Road Topology Problem—0
HeightLane: BEV Heightmap guided 3D Lane Detection—0
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