188 skills found · Page 1 of 7
mapbox / RobosatSemantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
MarvinTeichmann / KittiSegA Kitti Road Segmentation model implemented in tensorflow.
ydhongHIT / DDRNetThe official implementation of "Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes"
iwatake2222 / Self Driving Ish Computer Vision SystemThis project generates images you've probably seen in autonomous driving demo. Object Detection, Lane Detection, Road Segmentation, Depth Estimation using TensorRT
jkk-research / Urban Road FilterReal-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗
hlwang1124 / SNE RoadSegSNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020
xuanyuzhou98 / SqueezeSegV2Implementation of SqueezeSegV2, Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud
chenjun2hao / DDRNet.pytorchThis is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
Paulymorphous / SkeyenetRoad and Building Segmentation in Satellite Imagery
baidut / OpenVehicleVisionAn opensource lib. for vehicle vision applications (written by MATLAB), lane marking detection, road segmentation
chrise96 / 3D Ground SegmentationA ground segmentation algorithm for 3D point clouds based on the work described in “Fast segmentation of 3D point clouds: a paradigm on LIDAR data for Autonomous Vehicle Applications”, D. Zermas, I. Izzat and N. Papanikolopoulos, 2017. Distinguish between road and non-road points. Road surface extraction. Plane fit ground filter
anilbatra2185 / Road ConnectivityImproved Road Connectivity by Joint Learning of Orientation and Segmentation (CVPR2019)
cardwing / Codes For IntRA KDInter-Region Affinity Distillation for Road Marking Segmentation (CVPR 2020)
TonyXuQAQ / RNGDetPlusPlus[RAL 2023] RNGDet++: Road Network Graph Detection by Transformer with Instance Segmentation and Multi-scale Features Enhancement
NikolasEnt / Road Semantic SegmentationUdacity Self-Driving Car Engineer Nanodegree. Project: Road Semantic Segmentation
jaeoh2 / Road Lane Instance Segmentation PyTorchtuSimple dataset road lane instance segmentation with PyTorch, ROS, ENet, SegNet and Discriminative Loss.
jiankang1991 / Road Extraction Remote SensingRoad Extraction based on U-Net architecture (CVPR2018 DeepGlobe Challenge submission)
AHupuJR / RFNetRFNet: Real-time Fusion Network for RGB-D Semantic Segmentation Incorporating Unexpected Obstacle Detection of Road-driving Images
shjung13 / Standardized Max LogitsOfficial PyTorch implementation of paper: Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation (ICCV 2021 Oral Presentation)
venkanna37 / Label PixelsLabel-Pixels is the tool for semantic segmentation of remote sensing images using Fully Convolutional Networks. Initially, it is designed for extracting the road network from remote sensing imagery and now, it can be used to extract different features from remote sensing imagery.
