There are 1 repository under pointnet2 topic.
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
Pointnet++ modules implemented as tensorflow 2 keras layers.
A PyTorch Implementation of Pointnet++.
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"
Applying RandAugment on PointNet++
Code and Data for the paper "LPF-Defense: 3D Adversarial Defense based on Frequency Analysis", PLoS ONE
Efficient Point Cloud Upsampling and Normal Estimation using Deep Learning for Robust Surface Reconstruction
Semantic segmentation of LIDAR point clouds from the KITTI-360 dataset using a modified PointNet2. This is a Python and PyTorch based implementation using Jupyter Notebooks.
Prediction of vegetation coverage maps from High Density Lidar data, in a weakly supervised deep learning setting.
:sparkles: PointNet++ feature extractor and output heads implemented in TensorFlow 1.15 with Keras Models
Code for my masters thesis, "Deep Learning for Detecting Trees in the Urban Environment from Lidar"
Frustum Pointnet Implementation on KITTI and Lyft Dataset