PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

PyTorch implementation of Pointnet2/Pointnet++

[NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

[NeurIPS 2019, Spotlight] Point-Voxel CNN for Efficient 3D Deep Learning

Semantic3D segmentation with Open3D and PointNet++

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

[CVPR 2020, Oral] Category-Level Articulated Object Pose Estimation

A PyTorch Implementation of Pointnet++.

Pointnet++ modules implemented as tensorflow 2 keras layers.

A pointnet++ fork, with focus on semantic segmentation of differents datasets

PAPC is a deep learning for point clouds platform based on pure PaddlePaddle

This is the official pytorch implementation for paper: IF-Defense: 3D Adversarial Point Cloud Defense via Implicit Function based Restoration

A clean PointNet++ segmentation model implementation. Support batch of samples with different number of points.

Official implementation of the paper "Point Cloud Classification Using Content-based Transformer via Clustering in Feature Space"

GraspNet and Pointnet2/PointNet++ PyTorch Upgrade (v1.7.1 -> v1.13.1)

Applying RandAugment on PointNet++

Pytorch implementation of PointNeXt

Code and Data for the paper "LPF-Defense: 3D Adversarial Defense based on Frequency Analysis", PLoS ONE

A pytorch implementation of PointNet and PointNet++

Efficient Point Cloud Upsampling and Normal Estimation using Deep Learning for Robust Surface Reconstruction