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

Numpy-only dynamic object removal for LiDAR point clouds — 3D box crop + temporal filtering. No GPU, no 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…

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