1000 Open source projects that are alternatives of or similar to Pointnet

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Grid-GCN for Fast and Scalable Point Cloud Learning

A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)

PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)

3D point cloud datasets in HDF5 format, containing uniformly sampled 2048 points per shape.

Papers and Datasets about Point Cloud.

Keras implementation for Pointnet

PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling （CVPR 2020）

Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network

A lean C++ library for working with point cloud data

Differentiable Surface Splatting

Differentiable Point Cloud Sampling (CVPR 2020 Oral)

OpenMMLab Model Compression Toolbox and Benchmark.

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

A learned sampling approach for point clouds (CVPR 2019)

🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.

All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet

Generalized Data-free Universal Adversarial Perturbations

Tensorflow implementation : U-net and FCN with global convolution

The public CGAL repository, see the README below

《深度学习与计算机视觉》配套代码

Test Time Augmentation (TTA) wrapper for computer vision tasks: segmentation, classification, super-resolution, ... etc.

All-in-one Toolbox for Computer Vision Research.

PyTorch Implementation of Stacked U-Nets (SUNets)

PaddlePaddle End-to-End Development Toolkit（『飞桨』深度学习全流程开发工具）

deep learning for image processing including classification and object-detection etc.

Superpixel-based semantic segmentation, with object pose estimation and tracking. Provided as a ROS package.

A Python toolbox for computer vision research and project

3DMatch - a 3D ConvNet-based local geometric descriptor for aligning 3D meshes and point clouds.

This is an official implementation of our NeurIPS 2021 paper "HRFormer: High-Resolution Transformer for Dense Prediction".

Pytorch implementation of 'Graph Attention Convolution for Point Cloud Segmentation'

Pytorch framework for doing deep learning on point clouds.

3D Graph Neural Networks for RGBD Semantic Segmentation

Collection of computer vision models, ready to be included in a JVM project

Image Test Time Augmentation with PyTorch!

Semantic3D segmentation with Open3D and PointNet++

TF2 implementation of PointNet for segmenting point clouds

Crop/Weed Field Image Dataset

Caffe models (including classification, detection and segmentation) and deploy files for famouse networks

Sandbox for training deep learning networks

基于Tensorflow2开发的优秀扩展包及项目

Classification and Segmentation with Mask-RCNN of Skin Cancer using ISIC dataset

A python tool for fitting primitives 3D shapes in point clouds using RANSAC algorithm

Pytorch framework for doing deep learning on point clouds.

An open-source semi-automated processing chain for urban OBIA classification.

ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics

Geometric Adversarial Attacks and Defenses on 3D Point Clouds (3DV 2021)

Collections of model quantization algorithms

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

Resurces for MRI images processing and deep learning in 3D

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

Kaggle | 9th place single model solution for TGS Salt Identification Challenge

A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷

See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks (CVPR19)

Kaggle | 1st place solution for Freesound Audio Tagging 2019

Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"

A curated list of resources focused on Machine Learning in Geospatial Data Science.

KITTI data processing and 3D CNN for Vehicle Detection

A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.