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

Myria3D: Aerial Lidar HD Semantic Segmentation with Deep Learning

Open3D PointNet implementation with PyTorch

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

Attentional-PointNet is Deep-Neural-Network architecture for 3D object detection in 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".

New distributional and shape attacks on neural networks that process 3D point cloud data.

Chainer implementation of PointNet, PointNet++, KD-Network and 3DContextNework

Deep Hierarchical Encoder-Decoder with Point Atrous Convolution for Unorganized 3D Points