A list of papers and datasets about point cloud analysis (processing)

3DGS-to-PC: 3D Gaussian Splatting to Dense Point Clouds [3D-VAST: ICCVW 2025]

Papers, code and datasets about deep learning for 3D Object Detection.

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.

Morphing and Sampling Network for Dense Point Cloud Completion (AAAI2020)

Implementations of a rather simple version of the Iterative Closest Point algorithm in various languages.

Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions (RAL 2022)

C++ library and programs for reading and writing ASPRS LAS format with LiDAR data

Repo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296

[ICCV 2021] Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis

An SDK for multi-agent collaborative perception.

Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"

[NeurIPS2021] Learning Distilled Collaboration Graph for Multi-Agent Perception

[CVPR2023] Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration

PVT: Point-Voxel Transformer for 3D Deep Learning

Probabilistic line extraction from 2-D range scan

Introduction to Point Cloud Processing

Point cloud completion tool based on dictionary learning. Takes a PCL point cloud surface and fills in gaps or densifies sparse regions by learning from the various surface features of the cloud. This is done using a variation of the k-SVD dictionary learning algorithm that allows for continuous atoms and dealing with unstructured point cloud da…

Numpy-only dynamic object removal for LiDAR point clouds. 3D box crop + temporal filtering, ROS2 realtime node, public AV2 demos.

Utilities for point cloud processing. read ply, write ply, search nearest neighbors using octree ...