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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 26–50 of 54 papers

TitleStatusHype
Decoupling the Curve Modeling and Pavement Regression for Lane Detection—0
LATR: 3D Lane Detection from Monocular Images with TransformerCode2
GroupLane: End-to-End 3D Lane Detection with Channel-wise Grouping—0
Separated RoadTopoFormer—0
An Efficient Transformer for Simultaneous Learning of BEV and Lane Representations in 3D Lane Detection—0
TopoMask: Instance-Mask-Based Formulation for the Road Topology Problem via Transformer-Based Architecture—0
OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD MappingCode2
Graph-based Topology Reasoning for Driving ScenesCode2
Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane DetectionCode1
Sparse Point Guided 3D Lane Detection—0
BEV-LaneDet: An Efficient 3D Lane Detection Based on Virtual Camera via Key-PointsCode0
BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselineCode0
WS-3D-Lane: Weakly Supervised 3D Lane Detection With 2D Lane LabelsCode1
CurveFormer: 3D Lane Detection by Curve Propagation with Curve Queries and Attention—0
M^2-3DLaneNet: Exploring Multi-Modal 3D Lane Detection—0
3DLaneNAS: Neural Architecture Search for Accurate and Light-Weight 3D Lane DetectionCode0
MapTR: Structured Modeling and Learning for Online Vectorized HD Map ConstructionCode3
Reconstruct from BEV: A 3D Lane Detection Approach based on Geometry Structure Prior—0
Reconstruct from Top View: A 3D Lane Detection Approach based on Geometry Structure Prior—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
VectorMapNet: End-to-end Vectorized HD Map LearningCode2
PETRv2: A Unified Framework for 3D Perception from Multi-Camera ImagesCode3
ONCE-3DLanes: Building Monocular 3D Lane DetectionCode2
PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane BenchmarkCode2
Learning to Predict 3D Lane Shape and Camera Pose from a Single Image via Geometry ConstraintsCode1
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