[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
Python bindings for the Point Cloud Library (PCL)
C++ library and programs for reading and writing ASPRS LAS format with LiDAR data
A Modular Optimization framework for Localization and mApping (MOLA)
Drivers for receiving LiDAR data and more
Tool for convert files into Magicavoxel file
Research platform for 3D object detection in PyTorch.
Open Hardware scanning triangulation laser rangefinder
An unscented Kalman Filter implementation for fusing lidar and radar sensor measurements.
Full-python LiDAR SLAM using ICP and Scan Context
Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving
Extrinsic lidar camera calibration
This is a package for extrinsic calibration between a 3D LiDAR and a camera, described in paper: Improvements to Target-Based 3D LiDAR to Camera Calibration. This package is used for Cassie Blue's 3D LiDAR semantic mapping and automation.
PyTorch Implementation of PIXOR
Lidar camera calibration
Light-weight camera LiDAR calibration package for ROS using OpenCV and PCL (PnP + LM optimization)
chen2020iros: Learning an Overlap-based Observation Model for 3D LiDAR Localization.
Robust Odometry and Mapping for Multi-LiDAR Systems with Online Extrinsic Calibration
Awesome Robotic Tooling
Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.
SSL_SLAM2: Lightweight 3-D Localization and Mapping for Solid-State LiDAR (mapping and localization separated) ICRA 2021
A Python package for delineating nested surface depressions from digital elevation data.
LiDAR-Inertial 3D Plane Simulator
UrbanNav: an Open-Sourcing Localization Data Collected in Asian Urban Canyons, Including Tokyo and Hong Kong
A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways
LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain
Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.
Tools for analyzing aerial point clouds of forest data.
An "Iterative Closest Point" library for 2-D/3-D mapping in Robotics
Awesome Autonomous Driving Papers
This repository provides awesome research papers for autonomous driving perception. If you do find a problem or have any suggestions, please raise this as an issue or make a pull request with information (format of the repo): Research paper title, datasets, metrics, objects, source code, publisher, and year.
Read and write ASPRS las files, Rust edition.
Wetland Hydro Gee
Mapping wetland hydrological dynamics using Google Earth Engine (GEE)
Advanced implementation of LOAM
Lidar camera calibration
ROS package to find a rigid-body transformation between a LiDAR and a camera for "LiDAR-Camera Calibration using 3D-3D Point correspondences"
Complex Yolov4 Pytorch
The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"
🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving
SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)
The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.
R package for airborne LiDAR data manipulation and visualisation for forestry application