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

Pytorch framework for doing deep learning on point clouds.

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

Semantic3D segmentation with Open3D and PointNet++

Autoencoder for Point Clouds

PyTorch implementation of "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593

Open3D PointNet implementation with PyTorch

Myria3D: Aerial Lidar HD Semantic Segmentation with Deep Learning

Grid-GCN for Fast and Scalable Point Cloud Learning

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

Keras implementation for Pointnet

A Simple Point Cloud Registration Network based on PointNet.

A 3D plane detection approach using PointNet

Pointnet++ modules implemented as tensorflow 2 keras layers.

Attentional-PointNet is Deep-Neural-Network architecture for 3D object detection in point clouds

utilizing PointNet+ PCL for object detection, classification and pose estimation from point clouds

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.

Implementation for our CVPR 2021 oral paper "PointNetLK Revisited".