959 Open source projects that are alternatives of or similar to Pointnet2

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

Grid-GCN for Fast and Scalable Point Cloud Learning

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

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

Keras implementation for Pointnet

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Papers and Datasets about Point Cloud.

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

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

Crop/Weed Field Image Dataset

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

Sandbox for training deep learning networks

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

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

3D Graph Neural Networks for RGBD Semantic Segmentation

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

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

基于Tensorflow2开发的优秀扩展包及项目

OpenMMLab Model Compression Toolbox and Benchmark.

Pytorch framework for doing deep learning on point clouds.

TF2 implementation of PointNet for segmenting point clouds

A Python toolbox for computer vision research and project

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

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

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

Semantic3D segmentation with Open3D and PointNet++

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

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

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

Image Test Time Augmentation with PyTorch!

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

《深度学习与计算机视觉》配套代码

All-in-one Toolbox for Computer Vision Research.

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

Generalized Data-free Universal Adversarial Perturbations

Pytorch framework for doing deep learning on point clouds.

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

Tensorflow implementation : U-net and FCN with global convolution

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'

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

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

Resurces for MRI images processing and deep learning in 3D

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

Collections of model quantization algorithms

PyTorch Implementation of Stacked U-Nets (SUNets)

Darknet2ncnn converts the darknet model to the ncnn model

Snape is a convenient artificial dataset generator that wraps sklearn's make_classification and make_regression and then adds in 'realism' features such as complex formating, varying scales, categorical variables, and missing values.

This is a package for extrinsic calibration between a 3D LiDAR and a camera, described in paper: Improvements to Target-Based 3D LiDAR to Camera Calibration. This package is used for Cassie Blue's 3D LiDAR semantic mapping and automation.

Using pre trained word embeddings (Fasttext, Word2Vec)

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

Simple sign language alphabet recognizer using Python, openCV and tensorflow for training Inception model (CNN classifier).

[CVPR'19] JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

Transfer Learning for Anime Characters Recognition

A lightweight convolutional neural network

Implementation of EfficientNet model. Keras and TensorFlow Keras.

Code for a winning model (3 out of 419) in a Dstl Satellite Imagery Feature Detection challenge

Kaggle Segmentation Challenge

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language