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.

A Flask Application deployed over Google Cloud Platfrom to perform Advanced Lane Detection on Road Images which includes advanced image processing to detect lanes irrespective of the road texture, brightness, contrast, curves etc. Used Image warping and sliding window approach to find and plot the lane lines.

Road Dataset for semantic segmentation: extracted from Indian Driving Dataset

An autonomous navigation system for drones in both urban and rural environments.

Implements semantic segmentation of road surface using India Driving Dataset (IDD).

Self-Supervised Label Generator in MATLAB, IEEE RA-L

This repo contains a UNet based deep learning model for identifying roads from aerial images

Semantic segmentation for road detection using fully-convolutional network

This repository is the implementation of the "Bilateral Segmentation Network for Real-Time Semantic Segmentation" paper by Changqian Yu et al. which was published in ECCV 2018.

Simple road detection with Python and OpenCV

Neural network to predict and draw traffic lanes.