Lane Detection

Lane Detection is a computer vision task that involves identifying the boundaries of driving lanes in a video or image of a road scene. The goal is to accurately locate and track the lane markings in real-time, even in challenging conditions such as poor lighting, glare, or complex road layouts.

Lane detection is an important component of advanced driver assistance systems (ADAS) and autonomous vehicles, as it provides information about the road layout and the position of the vehicle within the lane, which is crucial for navigation and safety. The algorithms typically use a combination of computer vision techniques, such as edge detection, color filtering, and Hough transforms, to identify and track the lane markings in a road scene.

( Image credit: End-to-end Lane Detection )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 151–175 of 251 papers

Title	Date	Tasks	Status
Edge Device Deployment of Multi-Tasking Network for Self-Driving Operations	Oct 10, 2022	Autonomous DrivingDecoder	—Unverified
Efficient Road Lane Marking Detection with Deep Learning	Sep 11, 2018	Deep LearningLane Detection	—Unverified
Elastic Interaction Energy-Informed Real-Time Traffic Scene Perception	Oct 2, 2023	Autonomous DrivingImage Segmentation	—Unverified
ElasticLaneNet: An Efficient Geometry-Flexible Approach for Lane Detection	Dec 16, 2023	Lane Detection	—Unverified
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection	Jun 14, 2018	Lane DetectionSegmentation	—Unverified
End-to-End Deep Learning of Lane Detection and Path Prediction for Real-Time Autonomous Driving	Feb 9, 2021	Autonomous DrivingImage Segmentation	—Unverified
End-to-End Monocular Vanishing Point Detection Exploiting Lane Annotations	Aug 31, 2021	Camera CalibrationLane Detection	—Unverified
End-to-End Steering for Autonomous Vehicles via Conditional Imitation Co-Learning	Nov 25, 2024	Autonomous DrivingAutonomous Vehicles	—Unverified
End to End Video Segmentation for Driving : Lane Detection For Autonomous Car	Dec 13, 2018	Autonomous DrivingLane Detection	—Unverified
ENet-21: An Optimized light CNN Structure for Lane Detection	Mar 28, 2024	Autonomous VehiclesLane Detection	—Unverified
Experimental Analysis of Trajectory Control Using Computer Vision and Artificial Intelligence for Autonomous Vehicles	Jun 13, 2021	Autonomous VehiclesLane Detection	—Unverified
FastDraw: Addressing the Long Tail of Lane Detection by Adapting a Sequential Prediction Network	May 10, 2019	Autonomous VehiclesLane Detection	—Unverified
Federated Adversarial Learning for Robust Autonomous Landing Runway Detection	Jun 22, 2024	Federated LearningLane Detection	—Unverified
Focus on Local: Detecting Lane Marker from Bottom Up via Key Point	May 28, 2021	Lane Detection	—Unverified
Freespace Optical Flow Modeling for Automated Driving	Jul 29, 2023	Autonomous DrivingLane Detection	—Unverified
Geometric Constrained Joint Lane Segmentation and Lane Boundary Detection	Sep 1, 2018	Boundary DetectionLane Detection	—Unverified
GLane3D : Detecting Lanes with Graph of 3D Keypoints	Mar 31, 2025	3D Lane DetectionAutonomous Driving	—Unverified
GLane3D: Detecting Lanes with Graph of 3D Keypoints	Jan 1, 2025	3D Lane DetectionAutonomous Driving	—Unverified
GroupLane: End-to-End 3D Lane Detection with Channel-wise Grouping	Jul 18, 2023	3D Lane DetectionLane Detection	—Unverified
Hardware Acceleration of Lane Detection Algorithm: A GPU Versus FPGA Comparison	Dec 19, 2022	Autonomous DrivingEdge Detection	—Unverified
Heatmap-based Vanishing Point boosts Lane Detection	Jul 30, 2020	Autonomous DrivingImage Segmentation	—Unverified
HeightLane: BEV Heightmap guided 3D Lane Detection	Aug 15, 2024	3D Lane DetectionLane Detection	—Unverified
Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack	Sep 14, 2020	Lane Detection	—Unverified
HoughLaneNet: Lane Detection with Deep Hough Transform and Dynamic Convolution	Jul 7, 2023	Autonomous DrivingLane Detection	—Unverified
How to deal with glare for improved perception of Autonomous Vehicles	Apr 17, 2024	Autonomous DrivingAutonomous Vehicles	—Unverified

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All datasets CULane TuSimple CurveLanes BDD100K val LLAMAS nuScenes OpenLane Caltech Lanes Cordova Caltech Lanes Washington DET K-Lane OpenLane-V2 val

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DLNet	F1 score	81.23	—	Unverified
2	CLRerNet-DLA34	F1 score	81.12	—	Unverified
3	CLRerNet-Res101	F1 score	80.91	—	Unverified
4	CondLSTR(ResNet-101)	F1 score	80.77	—	Unverified
5	CLRerNet-Res34	F1 score	80.76	—	Unverified
6	CLRKDNet (DLA-34)	F1 score	80.68	—	Unverified
7	CLRNetV2 (DLA34)	F1 score	80.68	—	Unverified
8	CondLSTR(ResNet-34)	F1 score	80.55	—	Unverified
9	CLRNet(DLA-34)	F1 score	80.47	—	Unverified
10	CLRNetV2 (ResNet101)	F1 score	80.43	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SCNN_UNet_Attention_PL*	Accuracy	98.38	—	Unverified
2	GANet(ResNet-34)	F1 score	97.71	—	Unverified
3	GANet(ResNet-18)	F1 score	97.68	—	Unverified
4	CLRNet(ResNet-101)	F1 score	97.62	—	Unverified
5	GANet(ResNet-101)	F1 score	97.45	—	Unverified
6	CondLaneNet(ResNet-34)	F1 score	97.01	—	Unverified
7	CLRNetV2 (ResNet18)	Accuracy	96.99	—	Unverified
8	PE-RESA	Accuracy	96.93	—	Unverified
9	FOLOLane(ERFNet)	Accuracy	96.92	—	Unverified
10	CLRNet(ResNet-34)	Accuracy	96.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CondLSTR (ResNet-101)	F1 score	88.47	—	Unverified
2	CondLSTR (ResNet-34)	F1 score	88.23	—	Unverified
3	CondLSTR (ResNet-18)	F1 score	87.99	—	Unverified
4	CANet-L	F1 score	87.87	—	Unverified
5	CLRNetV2 (ResNet101)	F1 score	87.81	—	Unverified
6	CANet-M	F1 score	87.19	—	Unverified
7	CANet-S	F1 score	86.57	—	Unverified
8	CLRerNet-DLA34	F1 score	86.47	—	Unverified
9	CondLaneNet-L(ResNet-101)	F1 score	86.1	—	Unverified
10	CLRNet-DLA34	F1 score	86.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TwinLiteNetPlus-Large	IoU (%)	34.2	—	Unverified
2	TwinLiteNetPlus-Medium	IoU (%)	32.3	—	Unverified
3	HybridNets	IoU (%)	31.6	—	Unverified
4	TwinLiteNet	IoU (%)	31.08	—	Unverified
5	TriLiteNet-base	IoU (%)	29.8	—	Unverified
6	TwinLiteNetPlus-Small	IoU (%)	29.3	—	Unverified
7	A-YOLOM(s)	IoU (%)	28.8	—	Unverified
8	YOLOPv2	IoU (%)	27.25	—	Unverified
9	YOLOP	IoU (%)	26.2	—	Unverified
10	TwinLiteNetPlus-Nano	IoU (%)	23.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FENetV2	mF1	71.85	—	Unverified
2	CLRNet (DLA-34)	F1	0.96	—	Unverified
3	BézierLaneNet (ResNet-34)	F1	0.96	—	Unverified
4	LaneAF	F1	0.96	—	Unverified
5	CLRNet (ResNet-18)	F1	0.96	—	Unverified
6	BézierLaneNet (ResNet-18)	F1	0.96	—	Unverified
7	LaneATT (ResNet-34)	F1	0.94	—	Unverified
8	LaneATT (ResNet-122)	F1	0.94	—	Unverified
9	LaneATT (ResNet-18)	F1	0.93	—	Unverified
10	PolyLaneNet	F1	0.88	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DSLP	IoU	0.45	—	Unverified
2	LaneGraphNet	IoU	0.42	—	Unverified
3	STSU	IoU	0.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CondLSTR (ResNet-101)	F1 score	63.4	—	Unverified
2	CondLSTR (ResNet-34)	F1 score	62	—	Unverified
3	CondLSTR (ResNet-18)	F1 score	60.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VPGNet	F1	0.88	—	Unverified
2	Overfeat CNN detector + DBSCAN	F1	0.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VPGNet	F1	0.87	—	Unverified
2	Overfeat CNN detector + DBSCAN	F1	0.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LDNet	Average IOU	62.79	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LLDN-GFC	F1	82.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TopoLogic	mAP	33.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SCNN_UNet_Attention_PL*	F1	0.92	—	Unverified