Open-source alternatives to LibLAS.jl

CGAL is a software library that provides a comprehensive collection of computational geometry algorithms and data structures. It is built around a geometry kernel that defines fundamental geometric primitives and operations, enabling the construction of complex geometric objects and the computation of geometric predicates with exact arithmetic for reliable results. The library covers a wide range of geometric computation capabilities, including the construction of convex hulls, triangulations of point sets, and the generation of Voronoi diagrams. It also supports the processing of polygonal m

Point-e is a system for 3D model synthesis that generates three-dimensional point clouds from natural language descriptions and two-dimensional images. It utilizes diffusion models to synthesize these spatial representations based on text prompts or source images. The project includes specialized tools for refining these outputs, such as a point cloud upsampler to increase the density and resolution of low-resolution models. It also provides a mesh converter that uses distance function regression to transform raw point cloud data into structured 3D meshes. The broader capability surface cove

LIO-SAM is a lidar inertial SLAM framework and tightly-coupled sensor fusion pipeline. It functions as a factor graph optimization engine that combines lidar scans and inertial measurement unit data to build 3D point cloud maps and estimate robot trajectories. The system integrates global position factors to align local coordinates with real-world data. It employs loop closure detection to identify previously visited locations, creating constraints in the optimization graph to correct accumulated global drift. The framework covers lidar inertial odometry, point cloud processing, and trajecto

mmcv is a foundation library for computer vision based on PyTorch. It provides a comprehensive system for constructing convolutional neural networks, a toolkit for image and video preprocessing, and a collection of high-performance deep learning vision operators. The project is distinguished by its hardware-accelerated kernels for complex operations such as deformable convolutions and region pooling. It features a configuration-driven framework that allows for the dynamic instantiation of network layers and the registration of custom modules without modifying code. The library covers a broad

Implementation of SqueezeSeg, convolutional neural networks for LiDAR point clout segmentation

Deep Hough Voting for 3D Object Detection in Point Clouds

Entwine - point cloud organization for massive datasets

A Python package for delineating nested surface depressions from digital elevation data.

Draco is a library and toolset for compressing, transcoding, and decoding 3D geometric meshes and point cloud data. Its primary purpose is to reduce storage size and transmission bandwidth for 3D assets. The project includes a geometry optimizer specifically for glTF file containers to reduce asset footprints. It also features a hardened decoder designed to process malformed or untrusted 3D geometric data safely to prevent memory corruption and crashes. The software covers a broad range of 3D data processing capabilities, including geometric data reconstruction, point attribute management, a

The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.

Detect 6-DOF grasp poses in point clouds

A Julia Protocol for Geospatial Data

LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation

CloudCompare is a professional software application for processing and analyzing 3D point clouds and polygonal meshes. It functions as a 3D mesh analysis tool and a large dataset visualizer designed to display and manage millions of points in a 3D environment. The software provides specialized capabilities for point cloud comparison, utilizing an optimized octree structure to calculate spatial differences between two 3D datasets. This allows for the identification of variations and errors between point clouds or between a point cloud and a mesh. The system covers broad 3D data analysis areas

ICRA2021 A low-cost SLAM system based on camera and Livox lidar.

Work with points defined in various coordinate systems.

Remove then revert (IROS 2020)

Utilities for working with GeoJSON data in Julia

A library for spatially indexing kD bounding box data (based on libspatialindex)

NetCDF support for the julia programming language

Julia wrapper for the PROJ cartographic projections library

Fast and robust Voronoi & Delaunay tessellation creation with Julia

Image feature detection for the Julia language

Julia implementations of multidimensional array convolution and nonlinear stencil operations

An Iterative Closest Point (ICP) library for 2D and 3D mapping in Robotics