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 226–250 of 251 papers

Title	Date	Tasks	Status	Hype
Using DP Towards A Shortest Path Problem-Related Application	Mar 7, 2019	Autonomous DrivingLane Detection	—Unverified	0
Robust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks	Mar 6, 2019	Autonomous VehiclesLane Detection	CodeCode Available	0
End-to-end Lane Detection through Differentiable Least-Squares Fitting	Feb 1, 2019	Lane Detection	CodeCode Available	0
End to End Video Segmentation for Driving : Lane Detection For Autonomous Car	Dec 13, 2018	Autonomous DrivingLane Detection	—Unverified	0
3D-LaneNet: End-to-End 3D Multiple Lane Detection	Nov 26, 2018	3D Lane DetectionClustering	CodeCode Available	1
Efficient Road Lane Marking Detection with Deep Learning	Sep 11, 2018	Deep LearningLane Detection	—Unverified	0
Geometric Constrained Joint Lane Segmentation and Lane Boundary Detection	Sep 1, 2018	Boundary DetectionLane Detection	—Unverified	0
Multiple Lane Detection Algorithm Based on Optimised Dense Disparity Map Estimation	Aug 28, 2018	Disparity EstimationLane Detection	—Unverified	0
SafeDrive: Enhancing Lane Appearance for Autonomous and Assisted Driving Under Limited Visibility	Jul 24, 2018	Autonomous DrivingLane Detection	—Unverified	0
LineNet: a Zoomable CNN for Crowdsourced High Definition Maps Modeling in Urban Environments	Jul 16, 2018	Lane Detection	—Unverified	0
Real-time stereo vision-based lane detection system	Jul 8, 2018	CPUGPU	—Unverified	0
LaneNet: Real-Time Lane Detection Networks for Autonomous Driving	Jul 4, 2018	Autonomous DrivingEdge Classification	CodeCode Available	0
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection	Jun 14, 2018	Lane DetectionSegmentation	—Unverified	0
Real-time Lane Marker Detection Using Template Matching with RGB-D Camera	Jun 5, 2018	Autonomous DrivingLane Detection	—Unverified	0
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning	May 12, 2018	Autonomous DrivingDiversity	CodeCode Available	1
Learning to Cluster for Proposal-Free Instance Segmentation	Mar 17, 2018	Autonomous DrivingClustering	CodeCode Available	0
Towards End-to-End Lane Detection: an Instance Segmentation Approach	Feb 15, 2018	Instance SegmentationLane Detection	CodeCode Available	0
Spatial As Deep: Spatial CNN for Traffic Scene Understanding	Dec 17, 2017	Lane DetectionScene Understanding	CodeCode Available	0
VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition	Oct 17, 2017	Lane Detection	CodeCode Available	0
Semantic Instance Segmentation with a Discriminative Loss Function	Aug 8, 2017	Instance SegmentationLane Detection	CodeCode Available	0
Automated Lane Detection in Crowds using Proximity Graphs	Jul 6, 2017	Lane Detection	—Unverified	0
SafeDrive: A Robust Lane Tracking System for Autonomous and Assisted Driving Under Limited Visibility	Jan 29, 2017	Autonomous DrivingLane Detection	—Unverified	0
End to End Learning for Self-Driving Cars	Apr 25, 2016	Lane DetectionSelf-Driving Cars	CodeCode Available	2
Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving	Dec 7, 2015	Autonomous DrivingLane Detection	—Unverified	0
A Robust Lane Detection and Departure Warning System	Apr 28, 2015	Lane DetectionOptical Flow Estimation	—Unverified	0

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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