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Myria3D: Aerial Lidar HD Semantic Segmentation with Deep Learning
Visualize streams of multimodal data. Free, fast, easy to use, and simple to integrate. Built in Rust.
An extension of Open3D to address 3D Machine Learning tasks
Code release for Intensity Harmonization for Airborne LiDAR
OpenGF: An Ultra-Large-Scale Ground Filtering Dataset Built Upon Open ALS Point Clouds Around the World
[CVPR 2021, Oral] PREDATOR: Registration of 3D Point Clouds with Low Overlap.
Roof Classification, Segmentation, and Damage Completion using 3D Point Clouds
🔥Urban-scale point cloud dataset (CVPR 2021 & IJCV 2022)
A benchmark for point clouds registration algorithms
Polylidar3D - Fast polygon extraction from 3D Data
A Closer Look at Local Aggregation Operators in Point Cloud Analysis(ECCV 2020)
Kernel Point Convolution implemented in PyTorch
A fast and robust point cloud registration library
The NASA Ames Stereo Pipeline is a suite of automated geodesy & stereogrammetry tools designed for processing planetary imagery captured from orbiting and landed robotic explorers on other planets.
SPLATNet: Sparse Lattice Networks for Point Cloud Processing (CVPR2018)
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Deep Hough Voting for 3D Object Detection in Point Clouds
pyntcloud is a Python library for working with 3D point clouds.
Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.
a module for 3D semantic segmentation in point clouds.
PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud, CVPR 2019.
A list of papers and datasets about point cloud analysis (processing)
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
Graph Neural Network Library for PyTorch
Fully-Convolutional Point Networks for Large-Scale Point Clouds