1320 Repositories
Python point-cloud-segmentation Libraries
A simple Blog Using Django Framework and Used IBM Cloud Services for Text Analysis and Text to Speech
ElhamBlog Cloud Computing Course first assignment. A simple Blog Using Django Framework and Used IBM Cloud Services for Text Analysis and Text to Spee
Reimplementation of Dynamic Multi-scale filters for Semantic Segmentation.
Paddle implementation of Dynamic Multi-scale filters for Semantic Segmentation.
Cascading Feature Extraction for Fast Point Cloud Registration (BMVC 2021)
Cascading Feature Extraction for Fast Point Cloud Registration This repository contains the source code for the paper [Arxive link comming soon]. Meth
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr
Online Boutique is a cloud-native microservices demo application
Online Boutique is a cloud-native microservices demo application. Online Boutique consists of a 10-tier microservices application. The application is
This is an official source code for implementation on Extensive Deep Temporal Point Process
Extensive Deep Temporal Point Process This is an official source code for implementation on Extensive Deep Temporal Point Process, which is composed o
Hippocampal segmentation using the UNet network for each axis
Hipposeg Hippocampal segmentation using the UNet network for each axis, inspired by https://github.com/MICLab-Unicamp/e2dhipseg Red: False Positive Gr
Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python.
What is Retentioneering? Retentioneering is a Python framework and library to assist product analysts and marketing analysts as it makes it easier to
Pytorch implementation of paper "Learning Co-segmentation by Segment Swapping for Retrieval and Discovery"
SegSwap Pytorch implementation of paper "Learning Co-segmentation by Segment Swapping for Retrieval and Discovery" [PDF] [Project page] If our project
Pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"
About this repository This repo contains an Pytorch implementation for the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Netwo
A python app which aggregates and splits costs from multiple public cloud providers into a csv
Cloud Billing This project aggregates the costs public cloud resources by accounts, services and tags by importing the invoices from public cloud prov
TagLab: an image segmentation tool oriented to marine data analysis
TagLab: an image segmentation tool oriented to marine data analysis TagLab was created to support the activity of annotation and extraction of statist
Official PyTorch implementation of paper: Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation (ICCV 2021 Oral Presentation)
SML (ICCV 2021, Oral) : Official Pytorch Implementation This repository provides the official PyTorch implementation of the following paper: Standardi
Points2Surf: Learning Implicit Surfaces from Point Clouds (ECCV 2020 Spotlight)
Points2Surf: Learning Implicit Surfaces from Point Clouds (ECCV 2020 Spotlight)
DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction (3DV 2021)
DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction (3DV 2021) This repo is the implementation of DPC. Tested environment Pyth
This is the 3D Implementation of 《Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation》
CoraNet This is the 3D Implementation of 《Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation》 Environment pytor
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression Overview The ever-increasing 3D application makes the point cloud compression unprec
Detecting Blurred Ground-based Sky/Cloud Images
Detecting Blurred Ground-based Sky/Cloud Images With the spirit of reproducible research, this repository contains all the codes required to produce t
Official PyTorch implementation of paper: Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation (ICCV 2021 Oral Presentation)
SML (ICCV 2021, Oral) : Official Pytorch Implementation This repository provides the official PyTorch implementation of the following paper: Standardi
A Web API for automatic background removal using Deep Learning. App is made using Flask and deployed on Heroku.
Automatic_Background_Remover A Web API for automatic background removal using Deep Learning. App is made using Flask and deployed on Heroku. 👉 https:
Official PyTorch implementation of PICCOLO: Point-Cloud Centric Omnidirectional Localization (ICCV 2021)
Official PyTorch implementation of PICCOLO: Point-Cloud Centric Omnidirectional Localization (ICCV 2021)
FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
This repository contains the code accompanying the paper " FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation" Paper link: R
One implementation of the paper "DMRST: A Joint Framework for Document-Level Multilingual RST Discourse Segmentation and Parsing".
Introduction One implementation of the paper "DMRST: A Joint Framework for Document-Level Multilingual RST Discourse Segmentation and Parsing". Users
Copy Paste positive polyp using poisson image blending for medical image segmentation
Copy Paste positive polyp using poisson image blending for medical image segmentation According poisson image blending I've completely used it for bio
[ICCV 2021] A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation
[ICCV 2021] A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation
Kimimaro: Skeletonize Densely Labeled Images
Kimimaro: Skeletonize Densely Labeled Images # Produce SWC files from volumetric images. kimimaro forge labels.npy --progress # writes to ./kimimaro_o
30 Days of google cloud leaderboard website
30 Days of Cloud Leaderboard This is a leaderboard for the students of Thapar, Patiala who are participating in the 2021 30 days of Google Cloud Platf
Retinal vessel segmentation based on GT-UNet
Retinal vessel segmentation based on GT-UNet Introduction This project is a retinal blood vessel segmentation code based on UNet-like Group Transforme
Deep Learning as a Cloud API Service.
Deep API Deep Learning as Cloud APIs. This project provides pre-trained deep learning models as a cloud API service. A web interface is available as w
CORS Bypass Proxy Cloud Function
CORS Bypass Proxy Cloud Function
sysctl/sysfs settings on a fly for Kubernetes Cluster. No restarts are required for clusters and nodes.
SysBindings Daemon Little toolkit for control the sysctl/sysfs bindings on Kubernetes Cluster on the fly and without unnecessary restarts of cluster o
Official repo for BMVC2021 paper ASFormer: Transformer for Action Segmentation
ASFormer: Transformer for Action Segmentation This repo provides training & inference code for BMVC 2021 paper: ASFormer: Transformer for Action Segme
Wikipedia WordCloud App generate Wikipedia word cloud art created using python's streamlit, matplotlib, wikipedia and wordcloud packages
Wikipedia WordCloud App Wikipedia WordCloud App generate Wikipedia word cloud art created using python's streamlit, matplotlib, wikipedia and wordclou
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?"
DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re
The code is an implementation of Feedback Convolutional Neural Network for Visual Localization and Segmentation.
Feedback Convolutional Neural Network for Visual Localization and Segmentation The code is an implementation of Feedback Convolutional Neural Network
A PyTorch implementation of PointRend: Image Segmentation as Rendering
PointRend A PyTorch implementation of PointRend: Image Segmentation as Rendering [arxiv] [Official Implementation: Detectron2] This repo for Only Sema
Unet network with mean teacher for altrasound image segmentation
Unet network with mean teacher for altrasound image segmentation
Video Object Segmentation(VOS) From Zero to HeroVideo Object Segmentation(VOS) From Zero to Hero
Video Object Segmentation(VOS) From Zero to Hero! Goal 1:train a two layers cnn model for vos. Finish! see model.py FFNet for more diteal.(2021.9.30)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
"Domain Adaptive Semantic Segmentation without Source Data" (ACM MM 2021)
LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.
ADOP: Approximate Differentiable One-Pixel Point Rendering
ADOP: Approximate Differentiable One-Pixel Point Rendering Abstract: We present a novel point-based, differentiable neural rendering pipeline for scen
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
Official Implementation (PyTorch) of "Point Cloud Augmentation with Weighted Local Transformations", ICCV 2021
PointWOLF: Point Cloud Augmentation with Weighted Local Transformations This repository is the implementation of PointWOLF(To appear). Sihyeon Kim1*,
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
Swin Transformer for Semantic Segmentation of satellite images This repo contains the supported code and configuration files to reproduce semantic seg
Continuous Conditional Random Field Convolution for Point Cloud Segmentation
CRFConv This repository is the implementation of "Continuous Conditional Random Field Convolution for Point Cloud Segmentation" 1. Setup 1) Building c
The Official PyTorch Implementation of DiscoBox.
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision Paper | Project page | Demo (Youtube) | Demo (Bilib
Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation
Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation Paper Multi-Target Adversarial Frameworks for Domain Adaptation in
Posterior predictive distributions quantify uncertainties ignored by point estimates.
Posterior predictive distributions quantify uncertainties ignored by point estimates.
This is a simple bot that can be used to upload images to a third-party cloud (image hosting). Currently, only the imgbb.com website supports the bot. I Will do future updates
TGImageHosting This is a simple bot that can be used to upload images to a third party cloud (image hosting). Currently, only the imgbb.com website su
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation (NeurIPS2021 Benchmark and Dataset Track)
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh
Code for the paper SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection, ICIP 2021.
SphereRPN Code for the paper SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection, ICIP 2021. Authors: Th
Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021)
Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021) Alexey Nekrasov*, Jonas Schult*, Or Litany, Bastian Leibe, Francis Engelmann Mix3D is
LIVECell - A large-scale dataset for label-free live cell segmentation
LIVECell dataset This document contains instructions of how to access the data associated with the submitted manuscript "LIVECell - A large-scale data
Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation.
Unified-EPT Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation. Installation Linux, CUDA=10.0,
[ICCV 2021 Oral] SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer
This repository contains the source code for the paper SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer (ICCV 2021 Oral). The project page is here.
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision
a basic code repository for basic task in CV(classification,detection,segmentation)
basic_cv a basic code repository for basic task in CV(classification,detection,segmentation,tracking) classification generate dataset train predict de
Uses WiFi signals :signal_strength: and machine learning to predict where you are
Uses WiFi signals and machine learning (sklearn's RandomForest) to predict where you are. Even works for small distances like 2-10 meters.
MAASTA is a wrapper to create an Ansible inventory for MAAS instances that are provisioned by Terraform.
MAASTA is a wrapper to create an Ansible inventory for MAAS instances that are provisioned by Terraform.
GndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.
GndNet: Fast Ground plane Estimation and Point Cloud Segmentation for Autonomous Vehicles. Authors: Anshul Paigwar, Ozgur Erkent, David Sierra Gonzale
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
The Official PyTorch Implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
PyTorch implementation for View-Guided Point Cloud Completion
PyTorch implementation for View-Guided Point Cloud Completion
Float2Binary - A simple python class which finds the binary representation of a floating-point number.
Float2Binary A simple python class which finds the binary representation of a floating-point number. You can find a class in IEEE754.py file with the
This is a public repo where code samples are stored for the book Practical MLOps.
[Book-2021] Practical MLOps O'Reilly Book
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces(ICML 2021)
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces(ICML 2021) This repository contains the code
Work with the AWS IP address ranges in native Python.
Amazon Web Services (AWS) publishes its current IP address ranges in JSON format. Python v3 provides an ipaddress module in the standard library that allows you to create, manipulate, and perform operations on IPv4 and IPv6 addresses and networks. Wouldn't it be nice if you could work with the AWS IP address ranges like native Python objects?
DGCNN - Dynamic Graph CNN for Learning on Point Clouds
DGCNN is the author's re-implementation of Dynamic Graph CNN, which achieves state-of-the-art performance on point-cloud-related high-level tasks including category classification, semantic segmentation and part segmentation.
Write maintainable, production-ready pipelines using Jupyter or your favorite text editor. Develop locally, deploy to the cloud. ☁️
Write maintainable, production-ready pipelines using Jupyter or your favorite text editor. Develop locally, deploy to the cloud. ☁️
Perform oocyst segmentation in mercurochrome stained mosquito midgut
Midgut_oocyst_segmentation Perform oocyst segmentation in mercurochrome stained mosquito midguts This oocyst segmentation model also powers the webtoo
Confirm that files have been uploaded to Backblaze Cloud Backup successfully
Backblaze Backup Checker This Python script compares metadata captured from files within source folders against data parsed from Backblaze Cloud Backu
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
A 3D multi-modal medical image segmentation library in PyTorch We strongly believe in open and reproducible deep learning research. Our goal is to imp
Deep Multi-Magnification Network for multi-class tissue segmentation of whole slide images
Deep Multi-Magnification Network This repository provides training and inference codes for Deep Multi-Magnification Network published here. Deep Multi
PyTorch Implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedding (ORAL, MICCAIW 2021)
Small Lesion Segmentation in Brain MRIs with Subpixel Embedding PyTorch implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedd
Transfer-Learn is an open-source and well-documented library for Transfer Learning.
Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.
PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation (TPAMI).
PFENet This is the implementation of our paper PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation that has been accepted to IEE
Codes of paper "Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling"
Unseen Object Amodal Instance Segmentation (UOAIS) Seunghyeok Back, Joosoon Lee, Taewon Kim, Sangjun Noh, Raeyoung Kang, Seongho Bak, Kyoobin Lee This
An inofficial PyTorch implementation of PREDATOR based on KPConv.
PREDATOR: Registration of 3D Point Clouds with Low Overlap An inofficial PyTorch implementation of PREDATOR based on KPConv. The code has been tested
triggercmd is a CLI client for the TRIGGERcmd cloud service.
TriggerCMD CLI client triggercmd is a CLI client for the TRIGGERcmd cloud service. installation the triggercmd package is available in PyPI. to instal
A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.
PyTorch Project Template is being sponsored by the following tool; please help to support us by taking a look and signing up to a free trial PyTorch P
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm
Pytorch implementation of convolutional neural network visualization techniques
Convolutional Neural Network Visualizations This repository contains a number of convolutional neural network visualization techniques implemented in
Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)
Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim
End-to-end image segmentation kit based on PaddlePaddle.
English | 简体中文 PaddleSeg PaddleSeg has released the new version including the following features: Our team won the AutoNUE@CVPR 2021 challenge, where
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
Semi-supervised-learning-for-medical-image-segmentation. Recently, semi-supervised image segmentation has become a hot topic in medical image computin
Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)
Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim
An efficient 3D semantic segmentation framework for Urban-scale point clouds like SensatUrban, Campus3D, etc.
An efficient 3D semantic segmentation framework for Urban-scale point clouds like SensatUrban, Campus3D, etc.
Point Cloud Registration using Representative Overlapping Points.
Point Cloud Registration using Representative Overlapping Points (ROPNet) Abstract 3D point cloud registration is a fundamental task in robotics and c
Add filters (background blur, etc) to your webcam on Linux.
Add filters (background blur, etc) to your webcam on Linux.
CondNet: Conditional Classifier for Scene Segmentation
CondNet: Conditional Classifier for Scene Segmentation Introduction The fully convolutional network (FCN) has achieved tremendous success in dense vis
An extremely simple, intuitive, hardware-friendly, and well-performing network structure for LiDAR semantic segmentation on 2D range image. IROS21
FIDNet_SemanticKITTI Motivation Implementing complicated network modules with only one or two points improvement on hardware is tedious. So here we pr
An implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional Neural Network"
Retina Blood Vessels Segmentation This is an implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional
DeepLab resnet v2 model in pytorch
pytorch-deeplab-resnet DeepLab resnet v2 model implementation in pytorch. The architecture of deepLab-ResNet has been replicated exactly as it is from
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm
A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
A PyTorch implementation of V-Net Vnet is a PyTorch implementation of the paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Imag
Pixel-wise segmentation on VOC2012 dataset using pytorch.
PiWiSe Pixel-wise segmentation on the VOC2012 dataset using pytorch. FCN SegNet PSPNet UNet RefineNet For a more complete implementation of segmentati
A git extension for seeing your Cloud Build deployment
A git extension for seeing your Cloud Build deployment
Segmentation for medical image.
EfficientSegmentation Introduction EfficientSegmentation is an open source, PyTorch-based segmentation framework for 3D medical image. Features A whol