Popular GitHub Repositories for Road Warrior

? An exciting game of programming and Artificial Intelligence

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

A Kitti Road Segmentation model implemented in tensorflow.

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

Learn ML fundamentals for free.

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

Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles ?

Graph-based Topology Reasoning for Driving Scenes

Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).

Segment Anything Model for large-scale, vectorized road network extraction from aerial imagery. CVPRW 2024

Implementation of SqueezeSegV2, Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

Abnormal Human Behaviors Detection/ Road Accident Detection From Surveillance Videos/ Real-World Anomaly Detection in Surveillance Videos/ C3D Feature Extraction

This project is an aid to the blind. Till date there has been no technological advancement in the way the blind navigate. So I have used deep learning particularly convolutional neural networks so that they can navigate through the streets.

An opensource lib. for vehicle vision applications (written by MATLAB), lane marking detection, road segmentation

Self driving car AI in road fighter world

Inter-Region Affinity Distillation for Road Marking Segmentation (CVPR 2020)

RoadNet: A Multi-task Benchmark Dataset for Road Detection, TGRS.

Official implementation of the WACV 2025 paper "Pix2Poly: A Sequence Prediction Method for End-to-end Polygonal Building Footprint Extraction from Remote Sensing Imagery".

SafeDriveVision is a computer vision project aimed at enhancing road safety. This project leverages deep learning models to detect and alert in real-time the dangerous behaviors of drivers, such as using a phone while driving or showing signs of drowsiness.