A point cloud is a set of data points in space. The points represent a 3D shape or object. Each point has its set of X, Y and Z coordinates.
Open3D: A Modern Library for 3D Data Processing
Point Cloud Library (PCL)
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
A BVH implementation to speed up raycasting and enable spatial queries against three.js meshes.
Web labeling tool for bitmap images and point clouds
3D CAD viewer and converter based on Qt + OpenCascade
Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.
Reconstruct Watertight Meshes from Point Clouds [SIGGRAPH 2020]
A Three.js-based framework written in Javascript/WebGL for visualizing 3D geospatial data
😎 Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators.
loam code noted in Chinese（loam中文注解版）
[NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
Latent Point Diffusion Models for 3D Shape Generation
Efficient and parallel algorithms for point cloud registration [C++, Python]
3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling
Mesh processing library
LSD (LiDAR SLAM & Detection) is an open source perception architecture for autonomous vehicle/robotic
Image Signal Processing (ISP) Guide. Learn all about the process of converting an image/video into digital form by performing tasks like noise reduction, filtering, auto exposure, autofocus, HDR correction, and image sharpening with a Specialized type of media processor.