SqueezeSeg
LiDAR segmentation software
Implementation of SqueezeSeg, a deep neural network model for segmenting 3D LiDAR point clouds into road objects and other features
Implementation of SqueezeSeg, convolutional neural networks for LiDAR point clout segmentation
566 stars
27 watching
239 forks
Language: Python
last commit: over 5 years ago
Linked from 1 awesome list
autonomous-vehiclesdeep-neural-networkslidar-point-cloud
Related projects:
Repository | Description | Stars |
---|---|---|
edwardzhou130/polarseg | A PyTorch implementation of an online LiDAR point cloud segmentation neural network that provides near-real-time results | 378 |
tiagocortinhal/salsanext | A deep learning framework for real-time uncertainty-aware semantic segmentation of LiDAR point clouds for autonomous driving applications. | 415 |
prbonn/lidar-mos | This repository provides code and benchmarking tools for learning-based 3D LiDAR object segmentation using sequential data. | 602 |
peiyunh/opcseg | This project provides an implementation of an algorithm for optimal segmentation of 3D point clouds from LiDAR scans | 23 |
gsp-27/pytorch_squeezenet | A PyTorch implementation of the Squeezenet model with pre-trained weights on CIFAR 10 data for deep learning tasks. | 91 |
apburt/treeseg | Extracts individual trees from high-density lidar point clouds using machine learning and computer vision techniques | 214 |
zhengpeng7/birefnet | An implementation of a deep learning-based image segmentation model for high-resolution images | 1,319 |
prbonn/depth_clustering | A fast and robust algorithm to segment 3D point clouds generated by Velodyne sensors into objects. | 1,205 |
erogol/seg-torch | Custom image segmentation implementation using deep learning with Lua and Torch | 37 |
yu-changqian/torchseg | A toolkit for building and training semantic segmentation models using PyTorch. | 1,408 |
foamliu/deep-image-matting-pytorch | An implementation of deep image matting in PyTorch using a neural network architecture. | 817 |
nv-tlabs/gscnn | This code implements a neural network architecture designed to perform semantic segmentation in computer vision tasks. | 920 |
tramac/fast-scnn-pytorch | A PyTorch implementation of a deep learning model for semantic segmentation tasks in computer vision. | 381 |
imlab-uiip/lung-segmentation-2d | A deep learning model for segmenting lung tissue from 2D chest X-ray images using a UNet architecture. | 172 |
media-smart/vedaseg | A PyTorch-based toolbox for building and training semantic segmentation models | 410 |