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 201–225 of 251 papers

Title	Date	Tasks	Status	Hype
Ultra Fast Structure-aware Deep Lane Detection	Apr 24, 2020	Lane Detection	CodeCode Available	2
PolyLaneNet: Lane Estimation via Deep Polynomial Regression	Apr 23, 2020	Autonomous DrivingLane Detection	CodeCode Available	1
Traffic Lane Detection using FCN	Apr 19, 2020	DecoderLane Detection	—Unverified	0
Where can I drive? A System Approach: Deep Ego Corridor Estimation for Robust Automated Driving	Apr 16, 2020	Lane DetectionSemantic Segmentation	CodeCode Available	0
Inter-Region Affinity Distillation for Road Marking Segmentation	Apr 11, 2020	Knowledge DistillationLane Detection	CodeCode Available	1
Map-Enhanced Ego-Lane Detection in the Missing Feature Scenarios	Apr 2, 2020	Autonomous DrivingLane Detection	—Unverified	0
Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection	Mar 24, 2020	3D Lane DetectionImage Segmentation	CodeCode Available	1
Semi-Local 3D Lane Detection and Uncertainty Estimation	Mar 11, 2020	3D Lane DetectionLane Detection	—Unverified	0
Key Points Estimation and Point Instance Segmentation Approach for Lane Detection	Feb 16, 2020	Autonomous DrivingClustering	CodeCode Available	1
Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style Transfer	Feb 4, 2020	Lane DetectionMulti-Task Learning	CodeCode Available	1
Multi-lane Detection Using Instance Segmentation and Attentive Voting	Jan 1, 2020	Autonomous DrivingDecision Making	—Unverified	0
Lane Detection For Prototype Autonomous Vehicle	Dec 11, 2019	Autonomous VehiclesEdge Detection	—Unverified	0
Robust Lane Marking Detection Algorithm Using Drivable Area Segmentation and Extended SLT	Nov 20, 2019	Lane Detection	—Unverified	0
Dynamic Approach for Lane Detection using Google Street View and CNN	Sep 2, 2019	Autonomous NavigationDecoder	—Unverified	0
Copy-and-Paste Networks for Deep Video Inpainting	Aug 30, 2019	Image InpaintingLane Detection	CodeCode Available	0
Learning Lightweight Lane Detection CNNs by Self Attention Distillation	Aug 2, 2019	Knowledge DistillationLane Detection	CodeCode Available	0
Multi-Class Lane Semantic Segmentation using Efficient Convolutional Networks	Jul 22, 2019	Lane DetectionSegmentation	—Unverified	0
Lane Detection and Classification using Cascaded CNNs	Jul 2, 2019	Autonomous VehiclesClassification	CodeCode Available	0
Driver Behavior Analysis Using Lane Departure Detection Under Challenging Conditions	May 31, 2019	Lane DetectionObject	—Unverified	0
FastDraw: Addressing the Long Tail of Lane Detection by Adapting a Sequential Prediction Network	May 10, 2019	Autonomous VehiclesLane Detection	—Unverified	0
Deep Multi-Sensor Lane Detection	May 4, 2019	Autonomous DrivingLane Detection	—Unverified	0
Agnostic Lane Detection	May 2, 2019	Autonomous DrivingInstance Segmentation	—Unverified	0
Enhanced free space detection in multiple lanes based on single CNN with scene identification	May 2, 2019	Autonomous DrivingAutonomous Vehicles	CodeCode Available	0
Multiple Encoder-Decoders Net for Lane Detection	May 1, 2019	DecoderImage Segmentation	—Unverified	0
Deep Learning Based Automatic Video Annotation Tool for Self-Driving Car	Apr 19, 2019	CPUGeneral Classification	—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	CLRNet-DLA34	F1 score	86.1	—	Unverified
10	CondLaneNet-L(ResNet-101)	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