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Lane model
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Accuracy
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Automobiles, Data mining, Feature extraction, Image segmentation,
Neural networks, Remote sensing, Roads,
Cascaded convolutional neural network (CasNet), end-to-end,
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Estimation, Feature extraction, Image color analysis,
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vanishing point estimation
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Bertozzi, M.,
Cerri, P.,
Martins, F.N.,
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IEEE DOI
1802
Cameras, Laser radar, Roads, Robustness, Sensors, Visualization,
Autonomous driving, dead reckoning,
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1602
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John, V.[Vijay],
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Kidono, K.[Kiyosumi],
Mita, S.[Seiichi],
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ICPR18(189-194)
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1812
Roads, Feature extraction, Estimation, Regression tree analysis,
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Probabilistic lane estimation, Likelihood computation,
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IEEE DOI
1812
Image color analysis, Image segmentation, Image edge detection,
Roads, Gray-scale, Real-time systems, Robustness, Lane detection,
Kalman filter
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Zazo, S.[Santiago],
Justel, J.J.A.[José Juan Arranz],
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Road safety, Decision tree, Geometric design consistency,
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A Hardware Architecture for Cell-Based Feature-Extraction and
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Feature extraction, Computer architecture, Histograms, Training,
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Vision-based road slope estimation methods using road lines or local
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Proposals, Task analysis, Detectors, Feature extraction,
Benchmark testing, Real-time systems, Shape,
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Lane detection, Image quality, Convolution neural network
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WACV20(1823-1832)
IEEE DOI
2006
Roads, Image segmentation, Feature extraction, Machine learning,
Prediction algorithms, Parallel processing, Detectors
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Hu, C.,
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2007
Rollover, Stability analysis, Transient analysis, Tires, Safety,
Adaptation models, Autonomous vehicles, lane keeping,
rollover prevention
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Zhong, Y.Z.[Yu-Zhong],
Zhang, J.W.[Jian-Wei],
Li, Y.J.[Ying-Jiang],
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Ma, Y.[Yang],
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Semi-automated framework for generating cycling lane centerlines on
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Elsevier DOI
2008
Cycling lane, Centerline, Mobile LiDAR, Roadside barrier,
Object identification, Methodology
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Qian, Y.,
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Yang, M.,
DLT-Net: Joint Detection of Drivable Areas, Lane Lines, and Traffic
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IEEE DOI
2011
Task analysis, Decoding, Object detection, Semantics,
Intelligent vehicles, Roads, Neural networks, Multi-task network,
lane line detection
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Xiong, H.[Hui],
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Ravi, R.,
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Lin, Y.C.,
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Habib, A.,
Lane Width Estimation in Work Zones Using LiDAR-Based Mobile Mapping
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IEEE DOI
2012
Roads, Laser radar, Feature extraction,
Data mining, Surface morphology, Accidents, Lane width estimation,
wide lanes
BibRef
Wei, Y.,
Zhang, K.,
Ji, S.,
Simultaneous Road Surface and Centerline Extraction From Large-Scale
Remote Sensing Images Using CNN-Based Segmentation and Tracing,
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IEEE DOI
2012
Roads, Image segmentation, Remote sensing, Boosting,
Feature extraction, Surface topography, Semantics,
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Tang, J.G.[Ji-Gang],
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A review of lane detection methods based on deep learning,
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Elsevier DOI
2012
Lane detection, Deep learning, Semantic segmentation, Instance segmentation
BibRef
Lu, P.,
Xu, S.,
Peng, H.,
Graph-Embedded Lane Detection,
IP(30), 2021, pp. 2977-2988.
IEEE DOI
2102
Feature extraction, Lane detection, Topology, Fitting, Roads, Geometry,
Semantics, Lane detection, graph representation,
deep learning
BibRef
Zhang, Y.,
Lu, Z.,
Ma, D.,
Xue, J.H.,
Liao, Q.,
Ripple-GAN: Lane Line Detection With Ripple Lane Line Detection
Network and Wasserstein GAN,
ITS(22), No. 3, March 2021, pp. 1532-1542.
IEEE DOI
2103
Roads, Feature extraction, Semantics, Interference,
Training, Image segmentation, Lane line detection,
Ripple-GAN
BibRef
Zhu, D.[Di],
Song, R.[Rui],
Chen, H.[Hui],
Klette, R.[Reinhard],
Xu, Y.Y.[Yan-Yan],
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SP:IC(95), 2021, pp. 116230.
Elsevier DOI
2106
ADAS, Multi-lane detection, Multi-lane tracking, Moments, Kalman filter
BibRef
Xu, X.M.[Xue-Miao],
Yu, T.F.[Tian-Fei],
Hu, X.W.[Xiao-Wei],
Ng, W.W.Y.[Wing W. Y.],
Heng, P.A.[Pheng-Ann],
SALMNet: A Structure-Aware Lane Marking Detection Network,
ITS(22), No. 8, August 2021, pp. 4986-4997.
IEEE DOI
2108
Feature extraction, Roads, Convolution, Semantics, Benchmark testing,
Computer science, Convolutional neural networks,
intelligent transportation system
BibRef
Wen, T.[Tuopu],
Yang, D.[Diange],
Jiang, K.[Kun],
Yu, C.L.[Chun-Lei],
Lin, J.X.[Jia-Xin],
Wijaya, B.[Benny],
Jiao, X.Y.[Xin-Yu],
Bridging the Gap of Lane Detection Performance Between Different
Datasets: Unified Viewpoint Transformation,
ITS(22), No. 10, October 2021, pp. 6198-6207.
IEEE DOI
2110
Feature extraction, Robustness, Semantics, Adaptation models,
Task analysis, Deep learning, Lane detection,
advanced driver assistant systems (ADAS)
BibRef
Cheng, S.[Shuo],
Li, L.[Liang],
Liu, Y.G.[Yong-Gang],
Li, W.B.[Wei-Bing],
Guo, H.Q.[Hong-Qiang],
Virtual Fluid-Flow-Model-Based Lane-Keeping Integrated With Collision
Avoidance Control System Design for Autonomous Vehicles,
ITS(22), No. 10, October 2021, pp. 6232-6241.
IEEE DOI
2110
Roads, Collision avoidance, Vehicles, Mathematical model, Stress,
Vehicle dynamics, Virtual fluid-flow-model, lane-keeping,
path planning and tracking
BibRef
Haris, M.[Malik],
Hou, J.[Jin],
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Multi-scale spatial convolution algorithm for lane line detection and
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SP:IC(99), 2021, pp. 116413.
Elsevier DOI
2111
Unmanned vehicle, Lane line detection, Lane offset estimation,
Convolutional neural network (CNN), Scale perception, Multi-tasking
BibRef
Luo, S.[Sheng],
Zhang, X.Q.[Xiao-Qin],
Hu, J.[Jie],
Xu, J.H.[Jing-Hua],
Multiple Lane Detection via Combining Complementary Structural
Constraints,
ITS(22), No. 12, December 2021, pp. 7597-7606.
IEEE DOI
2112
Roads, Image edge detection, Transforms, Robustness, Lighting,
Feature extraction, Lane detection, Hough transform, dynamic programming
BibRef
Kang, C.M.[Chang Mook],
Kim, W.[Wonhee],
Linear Parameter Varying Observer for Lane Estimation Using Cylinder
Domain in Vehicles,
ITS(22), No. 11, November 2021, pp. 7030-7039.
IEEE DOI
2112
Observers, Roads, Cameras, Vision sensors, Tires, Autonomous vehicles,
Vehicle, lane change, state observer, cylinder domain
BibRef
Xiao, D.[Degui],
Zhuo, L.[Lin],
Li, J.[Jianfang],
Li, J.Z.[Jia-Zhi],
Structure-prior deep neural network for lane detection,
JVCIR(81), 2021, pp. 103373.
Elsevier DOI
2112
Lane marking detection, Deep neural network, Structure-prior
BibRef
Yin, R.[Ruochen],
Cheng, Y.[Yong],
Wu, H.[Huapeng],
Song, Y.T.[Yun-Tao],
Yu, B.[Biao],
Niu, R.X.[Run-Xin],
FusionLane: Multi-Sensor Fusion for Lane Marking Semantic
Segmentation Using Deep Neural Networks,
ITS(23), No. 2, February 2022, pp. 1543-1553.
IEEE DOI
2202
Semantics, Image segmentation, Cameras, Laser radar, Neural networks,
Meters, Lane marking, semantic segmentation, LIDAR-camera fusion,
LSTM
BibRef
Trogh, J.[Jens],
Botteldooren, D.[Dick],
de Coensel, B.[Bert],
Martens, L.[Luc],
Joseph, W.[Wout],
Plets, D.[David],
Map Matching and Lane Detection Based on Markovian Behavior, GIS, and
IMU Data,
ITS(23), No. 3, March 2022, pp. 2056-2070.
IEEE DOI
2203
Global Positioning System, Hidden Markov models, Trajectory,
Automobiles, Noise measurement, Map matching, lane detection, GPS,
data fusion
BibRef
Chen, S.[Sihan],
Huang, L.[Libo],
Chen, H.[Huanlei],
Bai, J.[Jie],
Multi-Lane Detection and Tracking Using Temporal-Spatial Model and
Particle Filtering,
ITS(23), No. 3, March 2022, pp. 2227-2245.
IEEE DOI
2203
Lane detection, Feature extraction, Geometry,
Computational modeling, Robustness, Roads, Radar tracking,
lane tracking
BibRef
Martirena, J.B.[Javier Barandiarán],
Doncel, M.N.[Marcos Nieto],
Vidal, A.C.[Andoni Cortés],
Madurga, O.O.[Oihana Otaegui],
Esnal, J.F.[Julián Flórez],
Romay, M.G.[Manuel Graña],
Automated Annotation of Lane Markings Using LIDAR and Odometry,
ITS(23), No. 4, April 2022, pp. 3115-3125.
IEEE DOI
2204
Annotations, Laser radar, Roads, Image segmentation, Manuals, Lasers,
Autonomous driving, lane sensing, lane detection, lane marking,
annotation
BibRef
Li, K.[Kan],
Yang, X.Y.[Xiao-Yu],
Luo, Y.H.[Yue-Hui],
Li, H.Y.[Hui-Yun],
Road geometry perception without accurate positioning and lane
information,
IET-ITS(16), No. 7, 2022, pp. 940-957.
DOI Link
2206
BibRef
Zhang, Y.C.[You-Cheng],
Lu, Z.Q.[Zong-Qing],
Zhang, X.C.[Xue-Chen],
Xue, J.H.[Jing-Hao],
Liao, Q.M.[Qing-Min],
Deep Learning in Lane Marking Detection: A Survey,
ITS(23), No. 7, July 2022, pp. 5976-5992.
IEEE DOI
2207
Deep learning, Feature extraction, Roads, Lighting, Semantics,
Optimization, Videos, Lane marking detection, traffic dataset,
evaluation metric
BibRef
Zhang, J.Y.[Ji-Yong],
Deng, T.[Tao],
Yan, F.[Fei],
Liu, W.B.[Wen-Bo],
Lane Detection Model Based on Spatio-Temporal Network With Double
Convolutional Gated Recurrent Units,
ITS(23), No. 7, July 2022, pp. 6666-6678.
IEEE DOI
2207
Lane detection, Feature extraction, Roads, Image segmentation,
Semantics, Logic gates, Deep learning, Lane detection, end-to-end,
convolutional neural network
BibRef
Shao, M.E.[Mei-En],
Haq, M.A.[Muhamad Amirul],
Gao, D.Q.[De-Qin],
Chondro, P.[Peter],
Ruan, S.J.[Shanq-Jang],
Semantic Segmentation for Free Space and Lane Based on Grid-Based
Interest Point Detection,
ITS(23), No. 7, July 2022, pp. 8498-8512.
IEEE DOI
2207
Task analysis, Image segmentation, Semantics, Neural networks,
Lane detection, Feature extraction, Object detection,
semantic segmentation
BibRef
Ko, Y.[Yeongmin],
Lee, Y.[Younkwan],
Azam, S.[Shoaib],
Munir, F.[Farzeen],
Jeon, M.[Moongu],
Pedrycz, W.[Witold],
Key Points Estimation and Point Instance Segmentation Approach for
Lane Detection,
ITS(23), No. 7, July 2022, pp. 8949-8958.
IEEE DOI
2207
Semantics, Feature extraction, Estimation, Training, Lane detection,
Image segmentation, Deep learning, Lane detection, deep learning
BibRef
Munir, F.[Farzeen],
Azam, S.[Shoaib],
Jeon, M.[Moongu],
Lee, B.G.[Byung-Geun],
Pedrycz, W.[Witold],
LDNet: End-to-End Lane Marking Detection Approach Using a Dynamic
Vision Sensor,
ITS(23), No. 7, July 2022, pp. 9318-9334.
IEEE DOI
2207
Cameras, Task analysis, Autonomous vehicles, Lane detection,
Decoding, Brightness, Feature extraction, Lane marking detection,
attention network
BibRef
Ren, F.L.[Feng-Lei],
Zhou, H.B.[Hai-Bo],
Yang, L.[Lu],
Liu, F.[Fulong],
He, X.[Xin],
ADPNet: Attention based dual path network for lane detection,
JVCIR(87), 2022, pp. 103574.
Elsevier DOI
2208
Lane detection, Semantic segmentation, Attention mechanism, Lane fitting
BibRef
Pang, G.L.[Gui-Lin],
Zhang, B.P.[Bao-Peng],
Teng, Z.[Zhu],
Ma, N.[Nan],
Fan, J.P.[Jian-Ping],
Fast-HBNet: Hybrid Branch Network for Fast Lane Detection,
ITS(23), No. 9, September 2022, pp. 15673-15683.
IEEE DOI
2209
Lane detection, Feature extraction, Semantics, Real-time systems,
Detectors, Representation learning, Roads, Lane detection,
hierarchical feature learning
BibRef
Zhou, Y.J.[Yu-Jing],
Wang, Z.J.[Ze-Jiang],
Wang, J.M.[Jun-Min],
Illumination-Resilient Lane Detection by Threshold Self-Adjustment
Using Newton-Based Extremum Seeking,
ITS(23), No. 10, October 2022, pp. 18643-18654.
IEEE DOI
2210
Image color analysis, Lane detection, Lighting, Cost function,
Image edge detection, Estimation, Feature extraction,
extremum seeking
BibRef
Yao, Z.Y.[Zi-Ying],
Wu, X.K.[Xin-Kai],
Wang, P.C.[Peng-Cheng],
Ding, C.[Chuan],
DevNet: Deviation Aware Network for Lane Detection,
ITS(23), No. 10, October 2022, pp. 17584-17593.
IEEE DOI
2210
Feature extraction, Lane detection, Estimation, Shape, Semantics,
Microprocessors, Autonomous vehicles, lane detection, driving assistance
BibRef
Yang, J.X.[Jia-Xing],
Zhang, L.[Lihe],
Lu, H.C.[Hu-Chuan],
Lane Detection with Versatile AtrousFormer and Local Semantic
Guidance,
PR(133), 2023, pp. 109053.
Elsevier DOI
2210
Lane detection, Global AtrousFormer, Local AtrousFormer,
Enhanced feature extractor, Local semantic guided decoder
BibRef
Katariya, V.[Vinit],
Baharani, M.[Mohammadreza],
Morris, N.[Nichole],
Shoghli, O.[Omidreza],
Tabkhi, H.[Hamed],
DeepTrack: Lightweight Deep Learning for Vehicle Trajectory
Prediction in Highways,
ITS(23), No. 10, October 2022, pp. 18927-18936.
IEEE DOI
2210
Trajectory, Predictive models, Computational modeling, Convolution,
Accidents, Deep learning, Real-time systems, DeepTrack
BibRef
Wang, Y.[Yuhao],
Wang, Y.H.[Yu-Hong],
Ho, I.W.H.[Ivan Wang-Hei],
Sheng, W.[Wei],
Chen, L.[Ling],
Pavement Marking Incorporated With Binary Code for Accurate
Localization of Autonomous Vehicles,
ITS(23), No. 11, November 2022, pp. 22290-22300.
IEEE DOI
2212
Roads, Location awareness, Autonomous vehicles,
Global Positioning System, Image color analysis, Cameras, binary code
BibRef
Qiu, Z.[Zengyu],
Zhao, J.[Jing],
Sun, S.L.[Shi-Liang],
MFIALane: Multiscale Feature Information Aggregator Network for Lane
Detection,
ITS(23), No. 12, December 2022, pp. 24263-24275.
IEEE DOI
2212
Lane detection, Feature extraction, Semantics, Task analysis,
Decoding, Mathematical models, Proposals, Deep learning, autonomous driving
BibRef
Zheng, S.[Shaowu],
Xie, Y.[Yun],
Li, M.H.[Ming-Hao],
Xie, C.[Chong],
Li, W.H.[Wei-Hua],
A Novel Strategy for Global Lane Detection Based on Key-Point
Regression and Multi-Scale Feature Fusion,
ITS(23), No. 12, December 2022, pp. 23244-23253.
IEEE DOI
2212
Feature extraction, Lane detection, Computational modeling,
Image segmentation, Image edge detection,
deep learning
BibRef
Han, Y.[Yi],
Wang, B.[Biyao],
Guan, T.[Tian],
Tian, D.[Di],
Yang, G.F.[Guang-Feng],
Wei, W.[Wei],
Tang, H.B.[Hong-Bo],
Chuah, J.H.[Joon Huang],
Research on Road Environmental Sense Method of Intelligent Vehicle
Based on Tracking Check,
ITS(24), No. 1, January 2023, pp. 1261-1275.
IEEE DOI
2301
For rainy day, cloudy day, night and other special scenarios.
Roads, Laser radar, Intelligent vehicles, Cameras,
Surface emitting lasers, Sorting, Visualization, machine vision
BibRef
Pittner, M.[Maximilian],
Condurache, A.[Alexandru],
Janai, J.[Joel],
3D-SpLineNet: 3D Traffic Line Detection using Parametric Spline
Representations,
WACV23(602-611)
IEEE DOI
2302
Measurement, Solid modeling, Shape, Lane detection, Roads, Lighting,
Applications: Robotics, 3D computer vision, visual reasoning
BibRef
Yang, Q.[Qin],
Ma, Y.H.[Ya-Hong],
Li, L.S.[Lin-Sen],
Su, C.[Chang],
Gao, Y.J.[Yu-Jie],
Tao, J.X.[Jia-Xin],
Huang, Z.T.[Zhen-Tao],
Jiang, R.[Rui],
Lightweight lane line detection based on learnable cluster
segmentation with self-attention mechanism,
IET-ITS(17), No. 3, 2023, pp. 518-529.
DOI Link
2303
BibRef
Niskanen, I.[Ilpo],
Kolli, T.[Tanja],
Immonen, M.[Matti],
Heikkilä, R.[Rauno],
Merisalo, V.[Virve],
Tyni, P.[Pekka],
Leviäkangas, P.[Pekka],
Non-Visual Sensing of Metallic Pavement Markers From a Moving Vehicle,
ITS(24), No. 3, March 2023, pp. 3352-3359.
IEEE DOI
2303
Roads, Metals, Snow, Detectors, Meteorology,
Magnetic resonance imaging, Ice, Metal detector, road marker,
winter
BibRef
Shi, P.C.[Pei-Cheng],
Zhang, C.H.[Cheng-Hui],
Xu, S.C.[Shu-Cai],
Qi, H.[Heng],
Chen, X.H.[Xin-He],
MT-Net: Fast video instance lane detection based on space time memory
and template matching,
JVCIR(91), 2023, pp. 103771.
Elsevier DOI
2303
Lane detection, Jitter, Space-time memory, Template matching, Error propagation
BibRef
Song, Y.C.[Yong-Chao],
Huang, T.[Tao],
Fu, X.[Xin],
Jiang, Y.[Yahong],
Xu, J.D.[Jin-Dong],
Zhao, J.D.[Jin-Dong],
Yan, W.Q.[Wei-Qing],
Wang, X.[Xuan],
A Novel Lane Line Detection Algorithm for Driverless Geographic
Information Perception Using Mixed-Attention Mechanism ResNet and Row
Anchor Classification,
IJGI(12), No. 3, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Zhou, J.[Jian],
Guo, Y.[Yuan],
Bian, Y.[Yaoan],
Huang, Y.Y.X.[Yuan-Yan-Xian],
Li, B.[Bijun],
Lane Information Extraction for High Definition Maps Using
Crowdsourced Data,
ITS(24), No. 7, July 2023, pp. 7780-7790.
IEEE DOI
2307
Roads, Data mining, Feature extraction, Information retrieval,
Automobiles, Satellites, Lane detection, Autonomous vehicles,
intelligent vehicles
BibRef
Yu, F.X.[Fu-Xing],
Wu, Y.F.[Ya-Feng],
Suo, Y.[Yina],
Su, Y.[Yaguang],
Shallow Detail and Semantic Segmentation Combined Bilateral Network
Model for Lane Detection,
ITS(24), No. 8, August 2023, pp. 8617-8627.
IEEE DOI
2308
Lane detection, Feature extraction, Semantic segmentation, Videos,
Task analysis, Convolution, Deep learning, Lane detection,
semantic segmentation
BibRef
Feng, Y.J.[Yun-Jian],
Li, J.[Jun],
Robust Accurate Lane Detection and Tracking for Automated
Rubber-Tired Gantries in a Container Terminal,
ITS(24), No. 10, October 2023, pp. 11254-11264.
IEEE DOI
2310
BibRef
Feng, Y.J.[Yun-Jian],
Zhou, K.Y.[Kun-Yang],
Li, J.[Jun],
Zhou, M.C.[Meng-Chu],
Incremental Learning-Based Lane Detection for Automated Rubber-Tired
Gantries in a Container Terminal,
CirSysVideo(34), No. 5, May 2024, pp. 3168-3179.
IEEE DOI
2405
Lane detection, Feature extraction, Task analysis, Training,
Adaptation models, Containers, Autonomous vehicles, rubber-tired gantry
BibRef
Ran, H.[Hao],
Yin, Y.F.[Yun-Fei],
Huang, F.[Faliang],
Bao, X.J.[Xian-Jian],
FLAMNet: A Flexible Line Anchor Mechanism Network for Lane Detection,
ITS(24), No. 11, November 2023, pp. 12767-12778.
IEEE DOI Code:
WWW Link.
2311
BibRef
Wu, Y.[Yuejian],
Zhao, L.Q.[Lin-Qing],
Lu, J.W.[Ji-Wen],
Yan, H.B.[Hai-Bin],
Dense Hybrid Proposal Modulation for Lane Detection,
CirSysVideo(33), No. 11, November 2023, pp. 6845-6859.
IEEE DOI Code:
WWW Link.
2311
BibRef
Li, X.L.[Xiao-Long],
Zhang, Y.[Yun],
Xiang, L.G.[Long-Gang],
Wu, T.[Tao],
Urban Road Lane Number Mining from Low-Frequency Floating Car Data
Based on Deep Learning,
IJGI(12), No. 11, 2023, pp. xx-yy.
DOI Link
2312
BibRef
Chae, Y.J.[Yeon Jeong],
Park, S.J.[So Jeong],
Kang, E.S.[Eun Su],
Chae, M.J.[Moon Ju],
Ngo, B.H.[Ba Hung],
Cho, S.I.[Sung In],
Point2Lane: Polyline-Based Reconstruction With Principal Points for
Lane Detection,
ITS(24), No. 12, December 2023, pp. 14813-14829.
IEEE DOI
2312
BibRef
Li, R.[Ruohan],
Dong, Y.Q.[Yong-Qi],
Robust Lane Detection Through Self Pre-Training With Masked
Sequential Autoencoders and Fine-Tuning With Customized PolyLoss,
ITS(24), No. 12, December 2023, pp. 14121-14132.
IEEE DOI
2312
BibRef
Patel, M.J.[Miral Jerambhai],
Kothari, A.M.[Ashish M.],
Deep Learning-Enabled Road Segmentation and Edge-Centerline Extraction
from High-Resolution Remote Sensing Images,
IJIG(23), No. 6 2023, pp. 2350058.
DOI Link
2312
BibRef
Song, Z.J.[Zhan-Jie],
Zhao, L.Q.[Lin-Qing],
Learning cross-task relations for panoptic driving perception,
PRL(176), 2023, pp. 89-95.
Elsevier DOI
2312
Panoptic driving perception, Multi-task learning,
Relation modeling, Object detection, Lane detection
BibRef
Li, Q.K.[Qian-Kun],
Yu, X.W.[Xian-Wang],
Chen, J.X.[Jun-Xin],
He, B.G.[Ben-Guo],
Wang, W.[Wei],
Rawat, D.B.[Danda B.],
Lyu, Z.H.[Zhi-Han],
PGA-Net: Polynomial Global Attention Network With Mean Curvature Loss
for Lane Detection,
ITS(25), No. 1, January 2024, pp. 417-429.
IEEE DOI Code:
WWW Link.
2402
Lane detection, Shape, Roads, Transformers, Mathematical models,
Computational modeling, Task analysis, Lane detection,
curvature loss
BibRef
Qin, Z.Q.[Ze-Qun],
Zhang, P.Y.[Peng-Yi],
Li, X.[Xi],
Ultra Fast Deep Lane Detection With Hybrid Anchor Driven Ordinal
Classification,
PAMI(46), No. 5, May 2024, pp. 2555-2568.
IEEE DOI Code:
WWW Link.
2404
Lane detection, Location awareness, Task analysis,
Feature extraction, Image segmentation, Lighting, Visualization,
anchor-driven ordinal classification
BibRef
Qin, Z.Q.[Ze-Qun],
Wang, H.Y.[Huan-Yu],
Li, X.[Xi],
Ultra Fast Structure-aware Deep Lane Detection,
ECCV20(XXIV:276-291).
Springer DOI
2012
BibRef
Gu, Y.C.[Yin-Chao],
Ma, C.[Chao],
Li, Q.[Qian],
Yang, X.K.[Xiao-Kang],
3D Lane Detection With Attention in Attention,
SPLetters(31), 2024, pp. 1104-1108.
IEEE DOI
2405
Feature extraction, Correlation, Lane detection, Data mining,
Cameras, Transformers, 3D Lane detection, attention mechanism, feature fusion
BibRef
Zhao, L.Q.[Lin-Qing],
Zheng, W.Z.[Wen-Zhao],
Zhang, Y.P.[Yun-P#1ng],
Zhou, J.[Jie],
Lu, J.W.[Ji-Wen],
StructLane: Leveraging Structural Relations for Lane Detection,
IP(33), 2024, pp. 3692-3706.
IEEE DOI Code:
WWW Link.
2406
Lane detection, Shape, Layout, Task analysis, Computational modeling,
Proposals, Feature extraction, Lane detection, shape modeling
BibRef
Khanmohammadi, F.[Fatemeh],
Azmi, R.[Reza],
Time-Series Anomaly Detection in Automated Vehicles Using D-CNN-LSTM
Autoencoder,
ITS(25), No. 8, August 2024, pp. 9296-9307.
IEEE DOI
2408
Anomaly detection, Deep learning, Long short term memory,
Time series analysis, Convolutional neural networks,
connected and automated vehicles (CAVs)
BibRef
Qiu, M.[Mei],
Christopher, L.[Lauren],
Chien, S.Y.P.[Stanley Yung-Ping],
Chen, Y.[Yaobin],
Intelligent Highway Adaptive Lane Learning System in Multiple ROIs of
Surveillance Camera Video,
ITS(25), No. 8, August 2024, pp. 8591-8601.
IEEE DOI Code:
WWW Link.
2408
BibRef
Wen, Y.X.[Yu-Xuan],
Yin, Y.F.[Yun-Fei],
Ran, H.[Hao],
FlipNet: An Attention-Enhanced Hierarchical Feature Flip Fusion
Network for Lane Detection,
ITS(25), No. 8, August 2024, pp. 8741-8750.
IEEE DOI
2408
Feature extraction, Lane detection, Message passing, Aggregates,
Task analysis, Data mining, Background noise, Lane detection,
intelligent transportation system
BibRef
Cheng, Q.[Qimin],
Ling, J.J.[Jia-Jun],
Yang, Y.F.[Yun-Fei],
Liu, K.[Kaiji],
Li, H.[Huanying],
Huang, X.[Xiao],
InstLane Dataset and Geometry-Aware Network for Instance Segmentation
of Lane Line Detection,
RS(16), No. 15, 2024, pp. 2751.
DOI Link
2408
BibRef
Zoljodi, A.[Ali],
Abadijou, S.[Sadegh],
Alibeigi, M.[Mina],
Daneshtalab, M.[Masoud],
Contrastive Learning for Lane Detection via cross-similarity,
PRL(185), 2024, pp. 175-183.
Elsevier DOI
2410
Contrastive learning, Lane detection, Convolutional neural networks
BibRef
Liu, B.[Binhui],
Ling, Q.[Qiang],
Hyper-Anchor Based Lane Detection,
ITS(25), No. 10, October 2024, pp. 13240-13252.
IEEE DOI
2410
Lane detection, Feature extraction, Task analysis, Convolution,
Autonomous vehicles, Accuracy, Visualization,
convolutional neural networks
BibRef
He, K.[Kaijie],
Xie, J.[Jun],
Dai, X.G.[Xin-Guang],
Chang, K.[Kenglun],
Chen, F.[Feng],
Wang, Z.[Zhepeng],
STADet: Streaming Timing-Aware Video Lane Detection,
CirSysVideo(34), No. 9, September 2024, pp. 8644-8656.
IEEE DOI
2410
Streaming media, Lane detection, Training, Task analysis,
Image segmentation, Feature extraction, Annotations,
automatic driving
BibRef
Zhou, K.[Kunyang],
Lane2Seq: Towards Unified Lane Detection via Sequence Generation,
CVPR24(16944-16953)
IEEE DOI
2410
Casting, Lane detection, Computational modeling,
Reinforcement learning, Computer architecture, Benchmark testing,
Lane2Seq
BibRef
Pittner, M.[Maximilian],
Janai, J.[Joel],
Condurache, A.P.[Alexandru P.],
LaneCPP: Continuous 3D Lane Detection Using Physical Priors,
CVPR24(10639-10648)
IEEE DOI
2410
Geometry, Knowledge engineering, Solid modeling, Analytical models,
Lane detection, 3D from single images, autonomous driving, deep learning
BibRef
Blayney, H.[Hugh],
Tian, H.L.[Han-Lin],
Scott, H.[Hamish],
Goldbeck, N.[Nils],
Stetson, C.[Chess],
Angeloudis, P.[Panagiotis],
Bézier Everywhere All at Once: Learning Drivable Lanes as Bézier
Graphs,
CVPR24(15365-15374)
IEEE DOI Code:
WWW Link.
2410
Head, Codes, Image edge detection, Predictive models, Transformers,
Real-time systems, Autonomous driving, Autonomous vehicles, DETR
BibRef
Zhou, J.X.[Jing-Xing],
Zhang, C.Z.[Chong-Zhe],
Beyerer, J.[Jürgen],
Towards Weakly-Supervised Domain Adaptation for Lane Detection,
SAIAD24(3553-3563)
IEEE DOI
2410
Training, Image segmentation, Adaptation models, Lane detection,
Trajectory planning, Supervised learning, Detectors
BibRef
Honda, H.[Hiroto],
Uchida, Y.[Yusuke],
CLRerNet: Improving Confidence of Lane Detection with LaneIoU,
WACV24(1165-1174)
IEEE DOI Code:
WWW Link.
2404
Measurement, Training, Protocols, Costs, Codes, Lane detection,
Algorithms, Image recognition and understanding, Applications,
Autonomous Driving
BibRef
Xiao, L.Y.[Ling-Yu],
Li, X.[Xiang],
Yang, S.[Sen],
Yang, W.K.[Wan-Kou],
ADNet: Lane Shape Prediction via Anchor Decomposition,
ICCV23(6381-6390)
IEEE DOI Code:
WWW Link.
2401
BibRef
Yao, C.T.[Cheng-Tang],
Yu, L.[Lidong],
Wu, Y.W.[Yu-Wei],
Jia, Y.D.[Yun-De],
Sparse Point Guided 3D Lane Detection,
ICCV23(8329-8338)
IEEE DOI
2401
BibRef
Jin, D.[Dongkwon],
Kim, D.[Dahyun],
Kim, C.S.[Chang-Su],
Recursive Video Lane Detection,
ICCV23(8439-8448)
IEEE DOI Code:
WWW Link.
2401
BibRef
Can, Y.B.[Yigit Baran],
Liniger, A.[Alexander],
Paudel, D.P.[Danda Pani],
Van Gool, L.J.[Luc J.],
Improving Online Lane Graph Extraction by Object-Lane Clustering,
ICCV23(8557-8567)
IEEE DOI
2401
BibRef
Chen, Z.[Ziye],
Liu, Y.[Yu],
Gong, M.M.[Ming-Ming],
Du, B.[Bo],
Qian, G.Q.[Guo-Qi],
Smith-Miles, K.[Kate],
Generating Dynamic Kernels via Transformers for Lane Detection,
ICCV23(6812-6821)
IEEE DOI
2401
BibRef
Luo, Y.[Yueru],
Zheng, C.[Chaoda],
Yan, X.[Xu],
Kun, T.[Tang],
Zheng, C.[Chao],
Cui, S.G.[Shu-Guang],
Li, Z.[Zhen],
LATR: 3D Lane Detection from Monocular Images with Transformer,
ICCV23(7907-7918)
IEEE DOI Code:
WWW Link.
2401
BibRef
Lv, Z.[Zinan],
Han, D.[Dong],
Wang, W.Z.[Wen-Zhe],
Chen, C.[Cheng],
IFPNet: Integrated Feature Pyramid Network with Fusion Factor for
Lane Detection,
ACVR23(1880-1889)
IEEE DOI
2401
BibRef
Wang, S.[Shan],
Nguyen, C.[Chuong],
Liu, J.W.[Jia-Wei],
Zhang, K.[Kaihao],
Luo, W.H.[Wen-Han],
Zhang, Y.[Yanhao],
Muthu, S.[Sundaram],
Maken, F.A.[Fahira Afzal],
Li, H.D.[Hong-Dong],
Homography Guided Temporal Fusion for Road Line and Marking
Segmentation,
ICCV23(1075-1085)
IEEE DOI
2401
BibRef
Huang, S.F.[Shao-Fei],
Shen, Z.W.[Zhen-Wei],
Huang, Z.[Zehao],
Ding, Z.H.[Zi-Han],
Dai, J.[Jiao],
Han, J.Z.[Ji-Zhong],
Wang, N.[Naiyan],
Liu, S.[Si],
Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane
Detection,
CVPR23(17451-17460)
IEEE DOI
2309
BibRef
Hu, Y.[Yao],
Du, X.Y.[Xin-Yu],
Jiang, S.[Shengbing],
Online LiDAR-to-Vehicle Alignment Using Lane Markings and Traffic
Signs,
VOCVALC23(3348-3357)
IEEE DOI
2309
BibRef
Büchner, M.[Martin],
Zürn, J.[Jannik],
Todoran, I.G.[Ion-George],
Valada, A.[Abhinav],
Burgard, W.[Wolfram],
Learning and Aggregating Lane Graphs for Urban Automated Driving,
CVPR23(13415-13424)
IEEE DOI
2309
BibRef
Dong, Y.P.[Yin-Peng],
Kang, C.X.[Cai-Xin],
Zhang, J.[Jinlai],
Zhu, Z.J.[Zi-Jian],
Wang, Y.K.[Yi-Kai],
Yang, X.[Xiao],
Su, H.[Hang],
Wei, X.X.[Xing-Xing],
Zhu, J.[Jun],
Benchmarking Robustness of 3D Object Detection to Common Corruptions
in Autonomous Driving,
CVPR23(1022-1032)
IEEE DOI
2309
BibRef
Cheng, Z.Y.[Zheng-Yun],
Zhang, G.W.[Guan-Wen],
Wang, C.H.[Chang-Hao],
Zhou, W.[Wei],
Dilane: Dynamic Instance-aware Network for Lane Detection,
ACCV22(II:124-140).
Springer DOI
2307
BibRef
Liu, R.X.[Rui-Xin],
Guan, Z.H.[Zhi-Hao],
Yuan, Z.[Zejian],
Liu, A.[Ao],
Zhou, T.[Tong],
Kun, T.[Tang],
Li, E.[Erlong],
Zheng, C.[Chao],
Mei, S.Q.[Shu-Qi],
Learning to Detect 3D Lanes by Shape Matching and Embedding,
WACV23(4280-4288)
IEEE DOI
2302
Training, Point cloud compression, Laser radar, Shape,
Lane detection, Network topology, Robotics
BibRef
Zhang, X.H.[Xiao-Han],
Wshah, S.[Safwan],
LanePainter: Lane Marks Enhancement via Generative Adversarial
Network,
ICPR22(3668-3675)
IEEE DOI
2212
Lane detection, Roads, Maintenance engineering, Benchmark testing,
Generative adversarial networks, Classification algorithms, Safety
BibRef
Zhang, H.[Han],
Gu, Y.C.[Yun-Chao],
Wang, X.L.[Xin-Liang],
Pan, J.J.[Jun-Jun],
Wang, M.H.[Ming-Hui],
Lane Detection Transformer Based on Multi-frame Horizontal and Vertical
Attention and Visual Transformer Module,
ECCV22(XXIX:1-16).
Springer DOI
2211
BibRef
Chen, L.[Li],
Sima, C.H.[Chong-Hao],
Li, Y.[Yang],
Zheng, Z.[Zehan],
Xu, J.J.[Jia-Jie],
Geng, X.W.[Xiang-Wei],
Li, H.Y.[Hong-Yang],
He, C.H.[Cong-Hui],
Shi, J.P.[Jian-Ping],
Qiao, Y.[Yu],
Yan, J.C.[Jun-Chi],
PersFormer: 3D Lane Detection via Perspective Transformer and the
OpenLane Benchmark,
ECCV22(XXXVIII:550-567).
Springer DOI
2211
BibRef
Xu, S.H.[Sheng-Hua],
Cai, X.Y.[Xin-Yue],
Zhao, B.[Bin],
Zhang, L.[Li],
Xu, H.[Hang],
Fu, Y.W.[Yan-Wei],
Xue, X.Y.[Xiang-Yang],
RCLane: Relay Chain Prediction for Lane Detection,
ECCV22(XXXVIII:461-477).
Springer DOI
2211
BibRef
Yang, H.[Hao],
Lin, S.Y.[Shu-Yuan],
Cheng, L.[Lin],
Lu, Y.[Yang],
Wang, H.Z.[Han-Zi],
SCINet: Semantic Cue Infusion Network for Lane Detection,
ICIP22(1811-1815)
IEEE DOI
2211
Image segmentation, Lane detection, Semantics, Benchmark testing,
Robustness, Copper, Task analysis, Lane detection, self attention
BibRef
Wang, J.S.[Jin-Sheng],
Ma, Y.C.[Yin-Chao],
Huang, S.F.[Shao-Fei],
Hui, T.R.[Tian-Rui],
Wang, F.[Fei],
Qian, C.[Chen],
Zhang, T.Z.[Tian-Zhu],
A Keypoint-based Global Association Network for Lane Detection,
CVPR22(1382-1391)
IEEE DOI
2210
Correlation, Shape, Lane detection, Navigation, Estimation,
Benchmark testing, Segmentation, grouping and shape analysis,
Navigation and autonomous driving
BibRef
Zheng, T.[Tu],
Huang, Y.F.[Yi-Fei],
Liu, Y.[Yang],
Tang, W.J.[Wen-Jian],
Yang, Z.[Zheng],
Cai, D.[Deng],
He, X.F.[Xiao-Fei],
CLRNet: Cross Layer Refinement Network for Lane Detection,
CVPR22(888-897)
IEEE DOI
2210
Location awareness, Cross layer design, Visualization,
Lane detection, Navigation, Machine vision, Semantics,
Navigation and autonomous driving
BibRef
Yan, F.[Fan],
Nie, M.[Ming],
Cai, X.Y.[Xin-Yue],
Han, J.H.[Jian-Hua],
Xu, H.[Hang],
Yang, Z.[Zhen],
Ye, C.Q.[Chao-Qiang],
Fu, Y.W.[Yan-Wei],
Mi, M.B.[Michael Bi],
Zhang, L.[Li],
ONCE-3DLanes: Building Monocular 3D Lane Detection,
CVPR22(17122-17131)
IEEE DOI
2210
Point cloud compression, Technological innovation,
Lane detection, Annotations, Roads, Layout, 3D from single images
BibRef
Sato, T.[Takami],
Chen, Q.A.[Qi Alfred],
Towards Driving-Oriented Metric for Lane Detection Models,
CVPR22(17132-17141)
IEEE DOI
2210
Measurement, Lane detection, Navigation, Machine vision, Robustness,
Natural language processing,
Vision applications and systems
BibRef
Jin, D.[Dongkwon],
Park, W.[Wonhui],
Jeong, S.G.[Seong-Gyun],
Kwon, H.[Heeyeon],
Kim, C.S.[Chang-Su],
Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse
Lanes,
CVPR22(17142-17150)
IEEE DOI
2210
Training, Image analysis, Codes, Navigation, Roads, Machine vision,
Navigation and autonomous driving,
Vision applications and systems
BibRef
Li, C.G.[Chen-Guang],
Zhang, B.[Boheng],
Shi, J.[Jia],
Cheng, G.L.[Guang-Liang],
Multi-level Domain Adaptation for Lane Detection,
WAD22(4379-4388)
IEEE DOI
2210
Costs, Lane detection, Shape, Image edge detection, Semantics
BibRef
Feng, Z.Y.[Zheng-Yang],
Guo, S.H.[Shao-Hua],
Tan, X.[Xin],
Xu, K.[Ke],
Wang, M.[Min],
Ma, L.Z.[Li-Zhuang],
Rethinking Efficient Lane Detection via Curve Modeling,
CVPR22(17041-17049)
IEEE DOI
2210
Deformable models, Convolutional codes, Image segmentation,
Lane detection, Detectors, Benchmark testing, Stability analysis,
Scene analysis and understanding
BibRef
Moujtahid, S.[Salma],
Benmokhtar, R.[Rachid],
Breheret, A.[Amaury],
Boukhdhir, S.E.[Saif-Eddine],
Spatial-UNet: Deep Learning-Based Lane Detection Using Fisheye Cameras
for Autonomous Driving,
CIAP22(II:576-586).
Springer DOI
2205
BibRef
Jin, Y.J.[Yu-Jie],
Ren, X.X.[Xiang-Xuan],
Chen, F.X.[Feng-Xiang],
Zhang, W.D.[Wei-Dong],
Robust Monocular 3D Lane Detection With Dual Attention,
ICIP21(3348-3352)
IEEE DOI
2201
Interpolation, Correlation, Lane detection, Image processing,
Aggregates, 3D lane detection, attention mechanism
BibRef
Lin, Y.C.[Yan-Cong],
Pintea, S.L.[Silvia-Laura],
van Gemert, J.C.[Jan C.],
Semi-Supervised Lane Detection With Deep Hough Transform,
ICIP21(1514-1518)
IEEE DOI
2201
Lane detection, Annotations, Image processing, Neural networks,
Layout, Transforms, Lane detection, Hough Transform, semi-supervised learning
BibRef
Meyer, A.[Annika],
Skudlik, P.[Philipp],
Pauls, J.H.[Jan-Hendrik],
Stiller, C.[Christoph],
YOLinO: Generic Single Shot Polyline Detection in Real Time,
AVVision21(2916-2925)
IEEE DOI
2112
Visualization, Image color analysis, Shape, Lane detection, Roads,
Urban areas, Object detection
BibRef
Shyam, P.[Pranjay],
Yoon, K.J.[Kuk-Jin],
Kim, K.S.[Kyung-Soo],
Weakly Supervised Approach for Joint Object and Lane Marking
Detection,
AVVision21(2885-2895)
IEEE DOI
2112
Performance evaluation, Training, Lane detection,
Image edge detection, Computer architecture, Object detection, Detectors
BibRef
Kim, B.D.[Byeoung-Do],
Park, S.H.[Seong Hyeon],
Lee, S.[Seokhwan],
Khoshimjonov, E.[Elbek],
Kum, D.[Dongsuk],
Kim, J.[Junsoo],
Kim, J.S.[Jeong Soo],
Choi, J.W.[Jun Won],
LaPred: Lane-Aware Prediction of Multi-Modal Future Trajectories of
Dynamic Agents,
CVPR21(14631-14640)
IEEE DOI
2111
Measurement, Dynamics, Semantics, Predictive models,
Feature extraction, Trajectory
BibRef
Qu, Z.[Zhan],
Jin, H.[Huan],
Zhou, Y.[Yang],
Yang, Z.[Zhen],
Zhang, W.[Wei],
Focus on Local: Detecting Lane Marker from Bottom Up via Key Point,
CVPR21(14117-14125)
IEEE DOI
2111
Training, Runtime, Shape, Training data, Predictive models,
Data models, Real-time systems
BibRef
Liu, R.J.[Rui-Jin],
Yuan, Z.J.[Ze-Jian],
Liu, T.[Tie],
Xiong, Z.L.[Zhi-Liang],
End-to-end Lane Shape Prediction with Transformers,
WACV21(3693-3701)
IEEE DOI
2106
Adaptation models, Shape, Lane detection, Roads, Process control,
Predictive models, Cameras
BibRef
Halfaoui, I.[Ibrahim],
Bouzaraa, F.[Fahd],
Urfalioglu, O.[Onay],
Li, M.Z.[Min-Zhen],
Real-time End-to-End Lane ID Estimation Using Recurrent Networks,
ICPR21(9304-9310)
IEEE DOI
2105
Location awareness, Visualization, Planing, Runtime, Roads, Semantics,
Estimation
BibRef
Cordes, K.[Kai],
Broszio, H.[Hellward],
Vehicle Lane Merge Visual Benchmark,
ICPR21(715-722)
IEEE DOI
2105
Location awareness, Visualization,
Target tracking, Shape, Trajectory planning, Benchmark testing
BibRef
Komori, H.[Hiroyuki],
Onoguchi, K.[Kazunori],
Lane Detection based on Object Detection and Image-to-image
Translation,
ICPR21(1075-1082)
IEEE DOI
2105
Image segmentation, Lane detection, Databases, Shape, Roads,
Object detection, Network architecture
BibRef
Chng, Z.M.[Zhe Ming],
Lew, J.M.H.[Joseph Mun Hung],
Lee, J.A.[Jimmy Addison],
RONELD: Robust Neural Network Output Enhancement for Active Lane
Detection,
ICPR21(6842-6849)
IEEE DOI
2105
Deep learning, Space vehicles, Lane detection,
Image edge detection, Roads, Neural networks, Real-time systems,
autonomous driving
BibRef
Ang, S.P.[Sui Paul],
Phung, S.L.[Son Lam],
Bouzerdoum, A.[Abdesselam],
Nguyen, T.N.A.[Thi Nhat Anh],
Duong, S.T.M.[Soan Thi Minh],
Schira, M.M.[Mark Matthias],
Real-time Pedestrian Lane Detection for Assistive Navigation using
Neural Architecture Search,
ICPR21(8392-8399)
IEEE DOI
2105
Image segmentation, Lane detection, Navigation, Neural networks,
Blindness, Tools, Real-time systems, Pedestrian lane detection,
deep learning
BibRef
Tabelini, L.[Lucas],
Berriel, R.[Rodrigo],
Paixão, T.M.[Thiago M.],
Badue, C.[Claudine],
de Souza, A.F.[Alberto F.],
Oliveira-Santos, T.[Thiago],
PolyLaneNet: Lane Estimation via Deep Polynomial Regression,
ICPR21(6150-6156)
IEEE DOI
2105
Measurement, Deep learning, Lane detection, Estimation, Cameras,
Real-time systems
BibRef
Garnett, N.[Noa],
Uziel, R.[Roy],
Efrat, N.[Netalee],
Levi, D.[Dan],
Synthetic-to-real Domain Adaptation for Lane Detection,
ACCV20(VI:52-67).
Springer DOI
2103
BibRef
Wang, B.K.[Bing-Ke],
Wang, Z.L.[Zi-Lei],
Zhang, Y.X.[Yi-Xin],
Polynomial Regression Network for Variable-number Lane Detection,
ECCV20(XVIII:719-734).
Springer DOI
2012
BibRef
Saqib, A.,
Sajid, S.,
Arif, S.M.,
Tariq, A.,
Ashraf, N.,
Domain Adaptation For Lane Marking: An Unsupervised Approach,
ICIP20(2381-2385)
IEEE DOI
2011
Decoding, Adaptation models, Image segmentation, Roads,
Machine learning, Training, Mathematical model, Domain Adaptation,
Convolutional Neural Network (CNN)
BibRef
Guo, Y.L.[Yu-Liang],
Chen, G.[Guang],
Zhao, P.[Peitao],
Zhang, W.[Weide],
Miao, J.[Jinghao],
Wang, J.[Jingao],
Choe, T.E.[Tae Eun],
GEN-Lanenet: A Generalized and Scalable Approach for 3d Lane Detection,
ECCV20(XXI:666-681).
Springer DOI
2011
BibRef
Yoo, S.,
Lee, H.S.[H. Seok],
Myeong, H.,
Yun, S.,
Park, H.,
Cho, J.,
Kim, D.H.[D. Hoon],
End-to-End Lane Marker Detection via Row-wise Classification,
AutoDrive20(4335-4343)
IEEE DOI
2008
Task analysis, Image segmentation, Computer architecture,
Semantics, Visualization, Spatial resolution, Computational complexity
BibRef
Philion, J.[Jonah],
FastDraw: Addressing the Long Tail of Lane Detection by Adapting a
Sequential Prediction Network,
CVPR19(11574-11583).
IEEE DOI
2002
BibRef
Chougule, S.[Shriyash],
Koznek, N.[Nora],
Ismail, A.[Asad],
Adam, G.[Ganesh],
Narayan, V.[Vikram],
Schulze, M.[Matthias],
Reliable Multilane Detection and Classification by Utilizing CNN as a
Regression Network,
ApolloScape18(V:740-752).
Springer DOI
1905
BibRef
Ghafoorian, M.[Mohsen],
Nugteren, C.[Cedric],
Baka, N.[Nóra],
Booij, O.[Olaf],
Hofmann, M.[Michael],
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane
Detection,
CVRoads18(I:256-272).
Springer DOI
1905
BibRef
Jung, J.[Jaehoon],
Che, E.[Erzhuo],
Olsen, M.J.[Michael J.],
Parrish, C.[Christopher],
Efficient and robust lane marking extraction from mobile lidar point
clouds,
PandRS(147), 2019, pp. 1-18.
Elsevier DOI
1901
Mobile laser scanning, Point cloud, Lane marking extraction
BibRef
Roberts, B.[Brook],
Kaltwang, S.[Sebastian],
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1012
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Earlier:
Robust lane detection and tracking with ransac and Kalman filter,
ICIP09(3261-3264).
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0911
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Lane Detection and Tracking Using a Layered Approach,
ACIVS09(474-484).
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0909
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0906
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0812
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0812
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Lipski, C.[Christian],
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0803
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Robust Lane Lines Detection and Quantitative Assessment,
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How Autonomous Mapping Can Help a Road Lane Detection System ?,
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0612
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0003
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Simultaneous Estimation of Pitch Angle and Lane Width
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ICIP99(II:31-35).
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Two Markov point processes for simulating line networks,
ICIP99(II:36-40).
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Yu, B., and
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ICPR92(I:224-227).
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Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Lane Changing, Lane-Change, Analysis, Control .