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
PyTorch implementation of "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593
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"
A Simple Point Cloud Registration Network based on PointNet.
Keras implementation for 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
This is the official pytorch implementation for paper: IF-Defense: 3D Adversarial Point Cloud Defense via Implicit Function based Restoration
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
A clean PointNet++ segmentation model implementation. Support batch of samples with different number of points.
GraspNet and Pointnet2/PointNet++ PyTorch Upgrade (v1.7.1 -> v1.13.1)
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