Popular GitHub Repositories for Lane Curvature

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

Unofficial implemention of lanenet model for real time lane detection

You Only Look Once for Panopitic Driving Perception.（MIR2022）

Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020)

Learning Lightweight Lane Detection CNNs by Self Attention Distillation (ICCV 2019)

PytorchAutoDrive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, RESA, LSTR, LaneATT, BézierLaneNet...) based on PyTorch with fast training, visualization, benchmarking & deployment help

Code for the paper entitled "Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection" (CVPR 2021)

End-to-end Lane Detection for Self-Driving Cars (ICCV 2019 Workshop)

[ECCV2020 Oral] Learning Lane Graph Representations for Motion Forecasting

VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition (ICCV 2017)

[ECCV 2022 Oral] Perspective Transformer on 3D Lane Detection

An open source advanced driver assistance system (ADAS) that uses Jetson Nano as the hardware. Features: Traffic sign detection, Forward collision warning, Lane departure warning.

This project generates images you've probably seen in autonomous driving demo. Object Detection, Lane Detection, Road Segmentation, Depth Estimation using TensorRT

[ICLR 2024] Map Learning with Lane Segment for Autonomous Driving

使用OpenCV部署全景驾驶感知网络YOLOP，可同时处理交通目标检测、可驾驶区域分割、车道线检测，三项视觉感知任务，包含C++和Python两种版本的程序实现。本套程序只依赖opencv库就可以运行， 从而彻底摆脱对任何深度学习框架的依赖。

The project can achieve FCWS, LDWS, and LKAS functions solely using only visual sensors. using YOLOv5 / YOLOv5-lite / YOLOv6 / YOLOv7 / YOLOv8 / YOLOv9 / EfficientDet and Ultra-Fast-Lane-Detection-v2 .

Code for "Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals," CoRL 2021.

Lane and obstacle detection for active assistance during driving. Uses windowed sweep for lane detection. Combination of object tracking and YOLO for obstacles. Determines lane change, relative velocity and time to collision

Ros node to use LaneNet to detect the lane in camera

[CVPRW 2024]Official PyTorch Implementation of "LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene Constraints"