957 Open source projects that are alternatives of or similar to Point2Sequence

Papers and Datasets about Point Cloud.

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

Grid-GCN for Fast and Scalable Point Cloud Learning

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

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

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

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

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

Keras implementation for Pointnet

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

A Python toolbox for computer vision research and project

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

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

OpenMMLab Model Compression Toolbox and Benchmark.

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

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

All-in-one Toolbox for Computer Vision Research.

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

Crop/Weed Field Image Dataset

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

Generalized Data-free Universal Adversarial Perturbations

Tensorflow implementation : U-net and FCN with global convolution

Collections of model quantization algorithms

Pytorch framework for doing deep learning on point clouds.

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

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

PyTorch Implementation of Stacked U-Nets (SUNets)

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

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

Semantic3D segmentation with Open3D and PointNet++

Pytorch framework for doing deep learning on point clouds.

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

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

TF2 implementation of PointNet for segmenting point clouds

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

Resurces for MRI images processing and deep learning in 3D

Image Test Time Augmentation with PyTorch!

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

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

《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.

Sandbox for training deep learning networks

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

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

3D Graph Neural Networks for RGBD Semantic Segmentation

基于Tensorflow2开发的优秀扩展包及项目

The Combined Anomalous Object Segmentation (CAOS) Benchmark

LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis, ICCV 2019, Seoul, Korea

A simple collection of well working NLP models (Keras, H2O, StarSpace) tuned and benchmarked on a variety of datasets.

Natural World Tasks

This repo introduces how to integrate Tensorflow framework into ROS with object detection API.

A basic framework for pulmonary nodule detection and characterization in CT

Efficient Online Transfer Learning for 3D Object Detection in Autonomous Driving

A tool for running deep learning algorithms for semantic segmentation with satellite imagery

A PyTorch Implementation of Fast-SCNN: Fast Semantic Segmentation Network(PyTorch >= 1.4)

Dictionary Learning for image processing

Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.

The PyTorch Implementation of F-ConvNet for 3D Object Detection

A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.

Ramp up your custom natural language processing (NLP) task, allowing you to bring your own data, use your preferred frameworks and bring models into production.