SalsaNext
LiDAR point cloud seg
A deep learning framework for real-time uncertainty-aware semantic segmentation of LiDAR point clouds for autonomous driving applications.
Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving
419 stars
19 watching
102 forks
Language: Python
last commit: almost 2 years agoLinked from 1 awesome list
3d-lidar-databayesian-networkdecoderencoderjaccardlidarlidar-point-cloudssemantic-segmentationsemantickitti
Related projects:
| Repository | Description | Stars |
|---|---|---|
| Provides pre-trained deep learning model for semantic segmentation of 3D point clouds using SalsaNext architecture | 14 | |
| Implementation of SqueezeSeg, a deep neural network model for segmenting 3D LiDAR point clouds into road objects and other features | 564 | |
| This project provides an implementation of an algorithm for optimal segmentation of 3D point clouds from LiDAR scans | 23 | |
| Large-scale point cloud semantic segmentation with graph-structured feature representation | 766 | |
| A PyTorch implementation of an online LiDAR point cloud segmentation neural network that provides near-real-time results | 382 | |
| A deep learning framework for unsupervised scene adaptation with memory regularization and pseudo label learning via uncertainty estimation | 387 | |
| A deep learning framework for efficient semantic segmentation of large-scale 3D point clouds | 1,327 | |
| Provides pre-trained and customizable semantic segmentation model in MATLAB | 23 | |
| Custom image segmentation implementation using deep learning with Lua and Torch | 37 | |
| A deep learning framework for 3D point cloud analysis, specifically for change detection and segmentation tasks. | 31 | |
| Develops semantic segmentation of satellite images using deep learning techniques | 10 | |
| Extracts individual trees from high-density lidar point clouds using machine learning and computer vision techniques | 216 | |
| A C++ library providing tools for segmenting point clouds from LiDAR data in ROS | 412 | |
| An efficient analysis tool for large point cloud datasets recorded over time | 44 | |
| A deep learning framework for semantic segmentation on edge devices. | 542 |