├── img └── Lane_Detection_Demo.jpg └── README.md /img/Lane_Detection_Demo.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DataXujing/awesome-lane-detection/master/img/Lane_Detection_Demo.jpg -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # awesome-lane-detection 2 | Lane Detection 3 | 4 | ![](img/Lane_Detection_Demo.jpg) 5 | 6 | [Paper](#Paper) 7 | 8 | - [2020](#2020) 9 | - [2019](#2019) 10 | - [2018](#2018) 11 | - [2017](#2017) 12 | 13 | [Code](#Code) 14 | 15 | [Blog/Tutorial](#Blog/Tutorial) 16 | 17 | [Datasets](#Datasets) 18 | 19 | # Paper 20 | 21 | ## 2020 22 | 23 | [ E2E-LMD: End-to-End Lane Marker Detection via Row-wise Classification](https://arxiv.org/abs/2005.08630) 24 | 25 | [SUPER: A Novel Lane Detection System](https://arxiv.org/abs/2005.07277) 26 | 27 | [Ultra Fast Structure-aware Deep Lane Detection](https://arxiv.org/abs/2004.11757) 28 | 29 | [PolyLaneNet: Lane Estimation via Deep Polynomial Regression](https://github.com/lucastabelini/PolyLaneNet) [github](https://github.com/lucastabelini/PolyLaneNet) 30 | 31 | [Inter-Region Affinity Distillation for Road Marking Segmentation](https://arxiv.org/abs/2004.05304) [github](https://github.com/cardwing/Codes-for-IntRA-KD) CVPR 2020 32 | 33 | [Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection](https://arxiv.org/abs/2003.10656) [Datasets](https://github.com/yuliangguo/3D_Lane_Synthetic_Dataset) 34 | 35 | [Detecting Lane and Road Markings at A Distance with Perspective Transformer Layers](https://arxiv.org/abs/2003.08550) 36 | 37 | [Semi-Local 3D Lane Detection and Uncertainty Estimation](https://arxiv.org/abs/2003.05257) 38 | 39 | [FusionLane: Multi-Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural Networks](https://arxiv.org/abs/2003.04404) [github](https://github.com/rolandying/FusionLane) 40 | 41 | [PINet：Key Points Estimation and Point Instance Segmentation Approach for Lane Detection](https://arxiv.org/abs/2002.06604) [github](https://github.com/koyeongmin/PINet) 42 | 43 | [Better-CycleGAN + ERFNet: Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style Transfer](https://arxiv.org/abs/2002.01177) submitted to IV 2020 44 | 45 | [Multi-lane Detection Using Instance Segmentation and Attentive Voting](https://arxiv.org/abs/2001.00236) ICCAS 2019 46 | 47 | ## 2019 48 | 49 | [Dynamic Approach for Lane Detection using Google Street View and CNN]() IEEE TENCON 2019 50 | 51 | [Learning Lightweight Lane Detection CNNs by Self Attention Distillation](https://arxiv.org/abs/1908.00821) [github](https://github.com/cardwing/Codes-for-Lane-Detection) ICCV 2019 52 | 53 | [Multi-Class Lane Semantic Segmentation using Efficient Convolutional Networks](https://arxiv.org/abs/1907.09438) MMSP 2019 54 | 55 | [Lane Detection and Classification using Cascaded CNNs](https://arxiv.org/abs/1907.01294) Eurocast 2019 56 | 57 | [Driver Behavior Analysis Using Lane Departure Detection Under Challenging Conditions](https://arxiv.org/abs/1906.00093) 58 | 59 | [FastDraw: Addressing the Long Tail of Lane Detection by Adapting a Sequential Prediction Network](https://arxiv.org/abs/1905.04354) CVPR 2019 60 | 61 | [Agnostic Lane Detection](https://arxiv.org/abs/1905.03704) [github](https://github.com/cardwing/Codes-for-Lane-Detection) 62 | 63 | [Deep Multi-Sensor Lane Detection](https://arxiv.org/abs/1905.01555) IROS2018 64 | 65 | [Enhanced free space detection in multiple lanes based on single CNN with scene identification](https://arxiv.org/abs/1905.00941) IV2019 [github](https://github.com/fabvio/ld-lsi/) 66 | 67 | [Robust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks](https://arxiv.org/abs/1903.02193) 68 | 69 | [End-to-end Lane Detection through Differentiable Least-Squares Fitting](https://arxiv.org/abs/1902.00293) [github](https://github.com/wvangansbeke/LaneDetection_End2End) 70 | 71 | ## 2018 72 | 73 | [End to End Video Segmentation for Driving : Lane Detection For Autonomous Car](https://arxiv.org/abs/1812.05914) 74 | 75 | [3D-LaneNet: end-to-end 3D multiple lane detection](https://arxiv.org/abs/1811.10203) ICCV 2019 76 | 77 | [Efficient Road Lane Marking Detection with Deep Learning](https://arxiv.org/abs/1809.03994) DSP 2018 78 | 79 | [Multiple Lane Detection Algorithm Based on Optimised Dense Disparity Map Estimation](https://arxiv.org/abs/1808.09128) IST 2018 80 | 81 | [LineNet: a Zoomable CNN for Crowdsourced High Definition Maps Modeling in Urban Environments](https://arxiv.org/abs/1807.05696) 82 | 83 | [Real-time stereo vision-based lane detection system](https://arxiv.org/abs/1807.02752) 84 | 85 | [LaneNet: Real-Time Lane Detection Networks for Autonomous Driving](https://arxiv.org/abs/1807.01726) 86 | 87 | [EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection](https://arxiv.org/abs/1806.05525) 88 | 89 | [Real-time Lane Marker Detection Using Template Matching with RGB-D Camera](https://arxiv.org/abs/1806.01621) 90 | 91 | [Towards End-to-End Lane Detection: an Instance Segmentation Approach](https://arxiv.org/abs/1802.05591) [论文解读](https://mp.weixin.qq.com/s/sGbSiCHpKjqKe9FP1ykjGw) [github](https://github.com/MaybeShewill-CV/lanenet-lane-detection) 92 | 93 | [Lane Detection and Classification for Forward Collision Warning System Based on Stereo Vision](https://ieeexplore.ieee.org/document/8353455/) 94 | 95 | [Advances in Vision-Based Lane Detection: Algorithms, Integration, Assessment, and Perspectives on ACP-Based Parallel Vision](https://ieeexplore.ieee.org/document/8332138/) 96 | 97 | [(SCNN)Spatial As Deep: Spatial CNN for Traffic Scene Understanding](https://arxiv.org/abs/1712.06080) AAAI 2018 [CSDN Translator](https://blog.csdn.net/u011974639/article/details/79580798?from=timeline#10006-weixin-1-52626-6b3bffd01fdde4900130bc5a2751b6d1) 98 | 99 | [Lane Detection Based on Inverse Perspective Transformation and Kalman Filter](http://itiis.org/digital-library/manuscript/file/1921/TIIS+Vol+12,+No+2-6.pdf) 100 | 101 | # 2017 102 | 103 | [A review of recent advances in lane detection and departure warning system](https://www.sciencedirect.com/science/article/pii/S0031320317303266) 104 | 105 | [Deep Learning Lane Marker Segmentation From Automatically Generated Labels](https://ieeexplore.ieee.org/document/7989163/) [Youtube](https://www.youtube.com/watch?v=AH01wpqqaeA) 106 | 107 | [VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition](http://openaccess.thecvf.com/content_iccv_2017/html/Lee_VPGNet_Vanishing_Point_ICCV_2017_paper.html) ICCV 2017 [github](https://github.com/SeokjuLee/VPGNet) 108 | 109 | # Code 110 | 111 | [Lane Detection（Paper with Code）](https://paperswithcode.com/task/lane-detection) 112 | 113 | 114 | 115 | 116 | 117 | https://github.com/wvangansbeke/LaneDetection_End2End 118 | 119 | 120 | 121 | 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 130 | 131 | ：Lane Detection with Deep Learning 132 | 133 | 134 | 135 | 136 | 137 | # Blog/Tutorial 138 | 139 | [Lane Detection with Deep Learning (Part 1)](https://towardsdatascience.com/lane-detection-with-deep-learning-part-1-9e096f3320b7) 140 | 141 | [Simple Lane Detection with OpenCV](https://medium.com/@mrhwick/simple-lane-detection-with-opencv-bfeb6ae54ec0) 142 | 143 | [Finding Lane Lines — Simple Pipeline For Lane Detection](https://towardsdatascience.com/finding-lane-lines-simple-pipeline-for-lane-detection-d02b62e7572b) 144 | 145 | [Building a lane detection system using Python 3 and OpenCV](https://medium.com/@galen.ballew/opencv-lanedetection-419361364fc0) 146 | 147 | [Tutorial: Build a lane detector](https://towardsdatascience.com/tutorial-build-a-lane-detector-679fd8953132) 148 | 149 | # Datasets 150 | 151 | [TuSimple](https://github.com/TuSimple/tusimple-benchmark) 152 | 153 | [CULane](https://xingangpan.github.io/projects/CULane.html) 154 | 155 | [BDD100K](http://bdd-data.berkeley.edu/) 156 | 157 | [Caltech](http://www.mohamedaly.info/datasets/caltech-lanes) 158 | 159 | [VPGNet](https://github.com/SeokjuLee/VPGNet#vpgnet-dataset) 160 | 161 | [3D Lane Synthetic Dataset](https://github.com/yuliangguo/3D_Lane_Synthetic_Dataset) 162 | 163 | [DIML](https://diml.yonsei.ac.kr/dataset/) 164 | 165 | [Jiqing Expressway](https://github.com/vonsj0210/Multi-Lane-Detection-Dataset-with-Ground-Truth) 166 | 167 | [A Dataset for Lane Instance Segmentation in Urban Environments](https://arxiv.org/abs/1807.01347) 168 | 169 | [The Lane Marker Dataset]() 170 | 171 | # Contact & Feedback 172 | 173 | If you have any suggestions about papers, feel free to mail me :) 174 | 175 | - [blog](http://www.cverblog.cn/) 176 | - [pull](https://github.com/amusi/awesome-lane-detection/pulls) --------------------------------------------------------------------------------