1204 Open source projects that are alternatives of or similar to Pointasnl

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

Keras implementation for Pointnet

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

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

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

Papers and Datasets about Point Cloud.

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

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

Crop/Weed Field Image Dataset

3D Graph Neural Networks for RGBD Semantic Segmentation

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

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

PyTorch Implementation of Stacked U-Nets (SUNets)

《深度学习与计算机视觉》配套代码

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

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

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

OpenMMLab Model Compression Toolbox and Benchmark.

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

Sandbox for training deep learning networks

A Python toolbox for computer vision research and project

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

Semantic3D segmentation with Open3D and PointNet++

Image Test Time Augmentation with PyTorch!

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

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

All-in-one Toolbox for Computer Vision Research.

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

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

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

Generalized Data-free Universal Adversarial Perturbations

Tensorflow implementation : U-net and FCN with global convolution

基于Tensorflow2开发的优秀扩展包及项目

TF2 implementation of PointNet for segmenting point clouds

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

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

Pytorch framework for doing deep learning on point clouds.

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

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

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

Pytorch framework for doing deep learning on point clouds.

Collections of model quantization algorithms

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

Angular 8 version of the Spring Petclinic sample application (frontend)

Get started with Semantic Segmentation based on Keras, including FCN32/FCN8/SegNet/U-Net

A lightweight convolutional neural network

Implementation of EfficientNet model. Keras and TensorFlow Keras.

Example Play Slick Project

LiTS - Liver Tumor Segmentation Challenge

EchoNet-Dynamic is a deep learning model for assessing cardiac function in echocardiogram videos.

Neural Point-Based Graphics

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

NLP research：基于tensorflow的nlp深度学习项目，支持文本分类/句子匹配/序列标注/文本生成 四大任务

Repository for my video series on building an iOS app in .NET.

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.

Entropy for Python

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.