Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020)
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Updated
Dec 14, 2022 - Python
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.
Semantically segment the road in the given image.
Implementation of the paper "ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data" in TensorFlow.
A practical implementation of pixel level segmentation based road detection and steering angle estimation methods.
Multi-Modal Multi-Task (3MT) Road Segmentation, IEEE RA-L 2023
This code segments out the drive-able portion of the road from the surrounding.
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
Road detection in satellite imagery using fully convolutional neural networks.
Simple road detection with Python and OpenCV
Neural network to predict and draw traffic lanes.
Autonomous Formula 1 by camera
This Project is Semantic Segmentation Project of Term 3 of Udacity Self-Driving Car Engineer Nanodegree.
This is a project to detect road signs using the Viola and jones Algorithm.
Road Lane Dection using OpenCV in python
Path/Road Following Differential Vehicle Bot.
Implementation of paper "Random-Walker Monocular Road Detection in Adverse Conditions Using Automated Spatiotemporal Seed Selection"
Semantic Segmentation with U-net and MobileUNETV2.
The goal of this project is to classify the roads of Switzerland based on the type of their surface, artificial or natural.
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