Lane Detection
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Benchmarks
CULane
TuSimple
CurveLanes
BDD100K val
LLAMAS
OpenLane
nuScenes
Caltech Lanes Cordova
Caltech Lanes Washington
DET
K-Lane
OpenLane-V2 val
tvtLane
Most implemented
End to End Learning for Self-Driving Cars
Towards End-to-End Lane Detection: an Instance Segmentation Approach
Ultra Fast Structure-aware Deep Lane Detection
Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
Spatial As Deep: Spatial CNN for Traffic Scene Understanding
Semantic Instance Segmentation with a Discriminative Loss Function
Papers
SIGMA-Lane: Scale-pyramId Gated MAmba for Temporally Consistent Video Lane Detection
Video lane detection requires predictions that remain stable across frames, yet severe vehicle occlusions can break temporal cues. In streaming recurrent models, corrupted observations may enter the hidden state and prod…
Lane DetectionCyclops: LiDAR as a Camera That Dreams in Color
Conventionally, robotic perception relies heavily on cameras due to the rich semantic texture they provide. However, their performance degrades significantly in low-light or high-dynamic-range environments. Conversely, w…
Semantic SegmentationLane DetectionBenchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective
Environmental illusions (eg., shadows, reflections, and tire marks) are naturally existing yet overlooked phenomena in real-world driving environments. They can disturb visual perception, leading to misinterpretation of …
Visual Question AnsweringAutonomous DrivingLane DetectionGFSR: Geometric Fidelity and Spatial Refinement for Reliable Lane Detection
Lane detection stands as a crucial perception task in autonomous driving and advanced driver assistance systems. However, existing methods still degrade in complex real scenarios due to two major limitations. First, clas…
Autonomous DrivingLane DetectionUnified Modeling of Lane and Lane Topology for Driving Scene Reasoning
Autonomous vehicles need to perceive not only physical elements in the driving scene, such as lane lines and traffic lights, but also logical elements like lane centerlines and their topology. Existing lane topology reas…
Autonomous VehiclesLane DetectionVision-Based Lane Following and Traffic Sign Recognition for Resource-Constrained Autonomous Vehicles
Autonomous vehicles (AVs) rely on real-time perception systems to understand road environments and ensure safe navigation. However, implementing reliable perception algorithms on resource-constrained embedded platforms r…
Traffic Sign RecognitionAutonomous VehiclesAutonomous DrivingLane Detection