Lane Detection
E2E-LMD: End-to-End Lane Marker Detection via Row-wise Classification
SUPER: A Novel Lane Detection System
Ultra Fast Structure-aware Deep Lane Detection github ECCV 2020
PolyLaneNet: Lane Estimation via Deep Polynomial Regression github
Inter-Region Affinity Distillation for Road Marking Segmentation github CVPR 2020
Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection github Datasets ECCV 2020
Detecting Lane and Road Markings at A Distance with Perspective Transformer Layers
Semi-Local 3D Lane Detection and Uncertainty Estimation
FusionLane: Multi-Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural Networks github
PINet：Key Points Estimation and Point Instance Segmentation Approach for Lane Detection github
Better-CycleGAN + ERFNet: Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style Transfer submitted to IV 2020
Multi-lane Detection Using Instance Segmentation and Attentive Voting ICCAS 2019
Dynamic Approach for Lane Detection using Google Street View and CNN IEEE TENCON 2019
Learning Lightweight Lane Detection CNNs by Self Attention Distillation github ICCV 2019
Multi-Class Lane Semantic Segmentation using Efficient Convolutional Networks MMSP 2019
Lane Detection and Classification using Cascaded CNNs Eurocast 2019
Driver Behavior Analysis Using Lane Departure Detection Under Challenging Conditions
FastDraw: Addressing the Long Tail of Lane Detection by Adapting a Sequential Prediction Network CVPR 2019
Agnostic Lane Detection github
Deep Multi-Sensor Lane Detection IROS2018
Enhanced free space detection in multiple lanes based on single CNN with scene identification IV2019 github
Robust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks
End-to-end Lane Detection through Differentiable Least-Squares Fitting github
End to End Video Segmentation for Driving : Lane Detection For Autonomous Car
3D-LaneNet: end-to-end 3D multiple lane detection ICCV 2019
Efficient Road Lane Marking Detection with Deep Learning DSP 2018
Multiple Lane Detection Algorithm Based on Optimised Dense Disparity Map Estimation IST 2018
LineNet: a Zoomable CNN for Crowdsourced High Definition Maps Modeling in Urban Environments
Real-time stereo vision-based lane detection system
LaneNet: Real-Time Lane Detection Networks for Autonomous Driving
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection
Real-time Lane Marker Detection Using Template Matching with RGB-D Camera
Towards End-to-End Lane Detection: an Instance Segmentation Approach 论文解读 github
Lane Detection and Classification for Forward Collision Warning System Based on Stereo Vision
(SCNN)Spatial As Deep: Spatial CNN for Traffic Scene Understanding AAAI 2018 CSDN Translator
Lane Detection Based on Inverse Perspective Transformation and Kalman Filter
A review of recent advances in lane detection and departure warning system
Deep Learning Lane Marker Segmentation From Automatically Generated Labels Youtube
VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition ICCV 2017 github
Lane Detection（Paper with Code）
https://github.com/cardwing/Codes-for-Lane-Detection
https://github.com/karstenBehrendt/unsupervised_llamas
https://github.com/wvangansbeke/LaneDetection_End2End
https://github.com/georgesung/advanced_lane_detection
https://github.com/MaybeShewill-CV/lanenet-lane-detection
https://github.com/XingangPan/SCNN
https://github.com/davidawad/Lane-Detection
https://github.com/yang1688899/CarND-Advanced-Lane-Lines
https://github.com/SeokjuLee/VPGNet
https://github.com/mvirgo/MLND-Capstone：Lane Detection with Deep Learning
https://github.com/galenballew/SDC-Lane-and-Vehicle-Detection-Tracking
https://github.com/shawshany/Advance_LaneFinding
Lane Detection with Deep Learning (Part 1)
Simple Lane Detection with OpenCV
Finding Lane Lines — Simple Pipeline For Lane Detection
Building a lane detection system using Python 3 and OpenCV
Tutorial: Build a lane detector
If you have any suggestions about papers, feel free to mail me :)