SNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020
Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗
Road Extraction based on U-Net architecture (CVPR2018 DeepGlobe Challenge submission)
Python scripts for performing road segemtnation and car detection using the HybridNets multitask model in ONNX.
Road Segmentation in Satellite Aerial Images
2D road segmentation using lidar data during training
Implementation of the paper "ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data" in TensorFlow.
🌱 SNE-RoadSeg in PyTorch, ECCV 2020 by Rui (Ranger) Fan & Hengli Wang, but now we have improved it.
使用OpenCV部署HybridNets，同时处理车辆检测、可驾驶区域分割、车道线分割，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， 彻底摆脱对任何深度学习框架的依赖。
Graph Reasoned Multi-Scale Road Segmentation in Remote Sensing Imagery
A course project for road segmentation using a U-Net Convolutional Neural Network on the KITTI ROAD 2013 dataset
YOLOPv2のPythonでのONNX推論サンプル
Multi-Modal Multi-Task (3MT) Road Segmentation, IEEE RA-L 2023
Segmenting satellite images of earth : determining which parts are roads.
Aerial Image segmentation using different EfficientNet based backbone encoders with UNet on Massachusetts Building and Road dataset
Road segmentation using CNNs
Identification of road surfaces and 12 different classes like speed bumps, paved, unpaved, markings, water puddles, potholes, etc.
Road Segmentation using Deep Learning
🎓 ML project for EPFL course CS-433 Machine Learning. Comparing ResNet and UNET for a road segmentation task.
This is my bachelor's thesis, which contains three main features: lane detection, road segmentation, and a Forward Collision Warning (FCW) system
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