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

SNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020

A Pytorch implementation of DeepCrack and RoadNet projects.

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

Semantically segment the road in the given image.

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

Official implementation of our ICRA'22 paper: SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous Driving

we present the plans of a driver-assistance system, which will be capable of road lane and traffic sign detection by using an OPEN-CV.

Implementation of the paper "ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data" in TensorFlow.

A Ground Mobile Robot Perception Dataset, IEEE RA-L & IEEE T-CYB

Scripts to process aerial imagery

Virtual Lane Boundary Generation for Human-Compatible Autonomous Driving

Involves the OpenCV based C++ implementation to detect and track roads for almost realtime performance

A practical implementation of pixel level segmentation based road detection and steering angle estimation methods.

Identification of road surfaces and 12 different classes like speed bumps, paved, unpaved, markings, water puddles, potholes, etc.

Multi-Modal Multi-Task (3MT) Road Segmentation, IEEE RA-L 2023

ENPM673: Project 2 Problem 2 and 3. In this project I detect the road lanes by performing image transformations on each frame of continuous input, further developing the program to also visually predict upcoming turns

This code segments out the drive-able portion of the road from the surrounding.

MASK-RCNN implementation for Lyft Perception Challenge

Road detection in satellite imagery using fully convolutional neural networks.