856 Repositories
Python scene-graph Libraries
Source code for our CVPR 2019 paper - PPGNet: Learning Point-Pair Graph for Line Segment Detection
PPGNet: Learning Point-Pair Graph for Line Segment Detection PyTorch implementation of our CVPR 2019 paper: PPGNet: Learning Point-Pair Graph for Line
Use graph-based analysis to re-classify stocks and to improve Markowitz portfolio optimization
Dynamic Stock Industrial Classification Use graph-based analysis to re-classify stocks and experiment different re-classification methodologies to imp
Dagon - An Asynchronous Task Graph Execution Engine
Dagon - An Asynchronous Task Graph Execution Engine Dagon is a job execution sys
A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks
Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of
This is the course project of AI3602: Data Mining of SJTU
This is the course project of AI3602: Data Mining of SJTU. Group Members include Jinghao Feng, Mingyang Jiang and Wenzhong Zheng.
2021 AI CUP Competition on Traditional Chinese Scene Text Recognition - Intermediate Contest
繁體中文場景文字辨識 程式碼說明 組別:這就是我 成員:蔣明憲 唐碩謙 黃玥菱 林冠霆 蕭靖騰 目錄 環境套件 安裝方式 資料夾布局 前處理-製作偵測訓練註解檔 前處理-製作分類訓練樣本 part.py : 從 json 裁切出分類訓練樣本 Class.py : 將切出來的樣本按照文字分類到各資料夾
Atomistic Line Graph Neural Network
Table of Contents Introduction Installation Examples Pre-trained models Quick start using colab JARVIS-ALIGNN webapp Peformances on a few datasets Use
Code for ICCV 2021 paper Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes using Scene Graphs
Graph-to-3D This is the official implementation of the paper Graph-to-3d: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphs | arx
This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures using receptive field analysis (RFA) and create graph visualizations of your architecture.
ReceptiveFieldAnalysisToolbox This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures usin
This repo includes some graph-based CTR prediction models and other representative baselines.
Graph-based CTR prediction This is a repository designed for graph-based CTR prediction methods, it includes our graph-based CTR prediction methods: F
Blender Add-on to Add Metal Materials to Your Scene
Blender QMM (Quick Metal Materials) Blender Addon to Add Metal Materials to Your Scene Installation Download the latest ZIP from Releases. Usage This
Security audit Python project dependencies against security advisory databases.
Security audit Python project dependencies against security advisory databases.
A Graph Neural Network Tool for Recovering Dense Sub-graphs in Random Dense Graphs.
PYGON A Graph Neural Network Tool for Recovering Dense Sub-graphs in Random Dense Graphs. Installation This code requires to install and run the graph
Towards Boosting the Accuracy of Non-Latin Scene Text Recognition
Convolutional Recurrent Neural Network + CTCLoss | STAR-Net Code for paper "Towards Boosting the Accuracy of Non-Latin Scene Text Recognition" Depende
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In
Official respository for "Band-limited Coordinate Networks for Multiscale Scene Representation"
BACON: Band-limited Coordinate Networks for Multiscale Scene Representation Project Page | Video | Paper Official PyTorch implementation of BACON. BAC
A simple version for graphfpn
GraphFPN: Graph Feature Pyramid Network for Object Detection Download graph-FPN-main.zip For training , run: python train.py For test with Graph_fpn
This is the official Pytorch-version code of FlatGCN (Flattened Graph Convolutional Networks for Recommendation).
FlatGCN This is the official Pytorch-version code of FlatGCN (Flattened Graph Convolutional Networks for Recommendation, submitted to ICASSP2022). Req
This application aims to read all wifi passwords and visualizes the complexity in graph formation by taking into account several criteria and help you generate new random passwords.
This application aims to read all wifi passwords and visualizes the complexity in graph formation by taking into account several criteria and help you generate new random passwords.
Bacon - Band-limited Coordinate Networks for Multiscale Scene Representation
BACON: Band-limited Coordinate Networks for Multiscale Scene Representation Proj
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et
This repository is for our paper Exploiting Scene Graphs for Human-Object Interaction Detection accepted by ICCV 2021.
SG2HOI This repository is for our paper Exploiting Scene Graphs for Human-Object Interaction Detection accepted by ICCV 2021. Installation Pytorch 1.7
Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21
Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose
A new codebase for Group Activity Recognition. It contains codes for ICCV 2021 paper: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition and some other methods.
Spatio-Temporal Dynamic Inference Network for Group Activity Recognition The source codes for ICCV2021 Paper: Spatio-Temporal Dynamic Inference Networ
Train Scene Graph Generation for Visual Genome and GQA in PyTorch = 1.2 with improved zero and few-shot generalization.
Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr
A library for graph deep learning research
Documentation | Paper [JMLR] | Tutorials | Benchmarks | Examples DIG: Dive into Graphs is a turnkey library for graph deep learning research. Why DIG?
A Telegram crawler to search groups and channels automatically and collect any type of data from them.
Introduction This is a crawler I wrote in Python using the APIs of Telethon months ago. This tool was not intended to be publicly available for a numb
Find graph motifs using intuitive notation
d o t m o t i f Find graph motifs using intuitive notation DotMotif is a library that identifies subgraphs or motifs in a large graph. It looks like t
Python library for parsing Godot scene files
Godot Parser This is a python library for parsing Godot scene (.tscn) and resource (.tres) files. It's intended to make it easier to automate certain
Code for paper "Multi-level Disentanglement Graph Neural Network"
Multi-level Disentanglement Graph Neural Network (MD-GNN) This is a PyTorch implementation of the MD-GNN, and the code includes the following modules:
Go from graph data to a secure and interactive visual graph app in 15 minutes. Batteries-included self-hosting of graph data apps with Streamlit, Graphistry, RAPIDS, and more!
✔️ Linux ✔️ OS X ❌ Windows (#39) Welcome to graph-app-kit Turn your graph data into a secure and interactive visual graph app in 15 minutes! Why This
Calibrated Hyperspectral Image Reconstruction via Graph-based Self-Tuning Network.
mask-uncertainty-in-HSI This repository contains the testing code and pre-trained models for the paper Calibrated Hyperspectral Image Reconstruction v
Fast Learning of MNL Model From General Partial Rankings with Application to Network Formation Modeling
Fast-Partial-Ranking-MNL This repo provides a PyTorch implementation for the CopulaGNN models as described in the following paper: Fast Learning of MN
SAFL: A Self-Attention Scene Text Recognizer with Focal Loss
SAFL: A Self-Attention Scene Text Recognizer with Focal Loss This repository implements the SAFL in pytorch. Installation conda env create -f environm
SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement
SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement This repository implements the approach described in SporeAgent: Reinforced
RodoSol-ALPR Dataset
RodoSol-ALPR Dataset This dataset, called RodoSol-ALPR dataset, contains 20,000 images captured by static cameras located at pay tolls owned by the Ro
This repository provides some of the code implemented and the data used for the work proposed in "A Cluster-Based Trip Prediction Graph Neural Network Model for Bike Sharing Systems".
cluster-link-prediction This repository provides some of the code implemented and the data used for the work proposed in "A Cluster-Based Trip Predict
STEFANN: Scene Text Editor using Font Adaptive Neural Network
STEFANN: Scene Text Editor using Font Adaptive Neural Network @ The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020.
PyTorch code for ICPR 2020 paper Future Urban Scene Generation Through Vehicle Synthesis
Future urban scene generation through vehicle synthesis This repository contains Pytorch code for the ICPR2020 paper "Future Urban Scene Generation Th
Code accompanying the paper Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs (Chen et al., CVPR 2020, Oral).
Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs This repository contains PyTorch implementation of our pa
Glyph-graph - A simple, yet versatile, package for graphing equations on a 2-dimensional text canvas
Glyth Graph Revision for 0.01 A simple, yet versatile, package for graphing equations on a 2-dimensional text canvas List of contents: Brief Introduct
A video scene detection algorithm is designed to detect a variety of different scenes within a video
Scene-Change-Detection - A video scene detection algorithm is designed to detect a variety of different scenes within a video. There is a very simple definition for a scene: It is a series of logically and chronologically related shots taken in a specific order to depict an over-arching concept or story.
Awesome Graph Classification - A collection of important graph embedding, classification and representation learning papers with implementations.
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers
Graph-total-spanning-trees - A Python script to get total number of Spanning Trees in a Graph
Total number of Spanning Trees in a Graph This is a python script just written f
Weakly- and Semi-Supervised Panoptic Segmentation (ECCV18)
Weakly- and Semi-Supervised Panoptic Segmentation by Qizhu Li*, Anurag Arnab*, Philip H.S. Torr This repository demonstrates the weakly supervised gro
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning Source code for AISTATS 2019 paper: Confidence-based Graph Convolutional Ne
Training neural models with structured signals.
Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured
Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Learning with Nonignorable Nonresponses‘
Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear
A Flexible Generative Framework for Graph-based Semi-supervised Learning (NeurIPS 2019)
G3NN This repo provides a pytorch implementation for the 4 instantiations of the flexible generative framework as described in the following paper: A
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
CCCL: Contrastive Cascade Graph Learning.
CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr
GitHub Activity Generator - A script that helps you instantly generate a beautiful GitHub Contributions Graph for the last year.
GitHub Activity Generator A script that helps you instantly generate a beautiful GitHub Contributions Graph for the last year. Before 😐 😶 😒 After ?
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N
PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE).
GRACE The official PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE). For a thorough resource collection of self-superv
Graph Representation Learning via Graphical Mutual Information Maximization
GMI (Graphical Mutual Information) Graph Representation Learning via Graphical Mutual Information Maximization (Peng Z, Huang W, Luo M, et al., WWW 20
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"
SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th
Pretraining on Dynamic Graph Neural Networks
Pretraining on Dynamic Graph Neural Networks Our article is PT-DGNN and the code is modified based on GPT-GNN Requirements python 3.6 Ubuntu 18.04.5 L
An implementation of Deep Graph Infomax (DGI) in PyTorch
DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom
Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)
Unsupervised Attributed Multiplex Network Embedding (DMGI) Overview Nodes in a multiplex network are connected by multiple types of relations. However
Heterogeneous Deep Graph Infomax
Heterogeneous-Deep-Graph-Infomax Parameter Setting: HDGI-A: Node-level dimension: 16 Attention head: 4 Semantic-level attention vector: 8 learning rat
Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"
Subg-Con Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning (Jiao et al., ICDM 2020): https://arxiv.org/abs/2009.10273 Over
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu
A Python server and client app that tracks player session times and server status
MC Outpost A Python server and client application that tracks player session times and server status About MC Outpost provides a session graph and ser
Scientific measurement library for instruments, experiments, and live-plotting
PyMeasure scientific package PyMeasure makes scientific measurements easy to set up and run. The package contains a repository of instrument classes a
The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution
Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe
Source code of the "Graph-Bert: Only Attention is Needed for Learning Graph Representations" paper
Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.
Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training
PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
Pre-training of Graph Augmented Transformers for Medication Recommendation
G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be
Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa
Deeper insights into graph convolutional networks for semi-supervised learning
deeper_insights_into_GCNs Deeper insights into graph convolutional networks for semi-supervised learning References data and utils.py come from Implem
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels"
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels" Please refer to htt
code for "Self-supervised edge features for improved Graph Neural Network training", arxivlink
Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages
DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program
Code for hyperboloid embeddings for knowledge graph entities
Implementation for the papers: Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs, Nurendra Choudhary, Nikhil Rao,
Code for the paper: Audio-Visual Scene Analysis with Self-Supervised Multisensory Features
[Paper] [Project page] This repository contains code for the paper: Andrew Owens, Alexei A. Efros. Audio-Visual Scene Analysis with Self-Supervised Mu
Scene-Text-Detection-and-Recognition (Pytorch)
Scene-Text-Detection-and-Recognition (Pytorch) Competition URL: https://tbrain.t
The code for SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network.
SAG-DTA The code is the implementation for the paper 'SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network'. Requirements py
Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition (AGRA, ACM 2020, Oral)
Cross Domain Facial Expression Recognition Benchmark Implementation of papers: Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchm
An add to make adding screenshots and copied images to the scene easy
Blender Clipboard to Scene It doesn't work with version 2.93 and higher (I tested it on 2.91 and 2.83) There is an issue with importing the Pillow mod
The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding"
AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:
Build a medical knowledge graph based on Unified Language Medical System (UMLS)
UMLS-Graph Build a medical knowledge graph based on Unified Language Medical System (UMLS) Requisite Install MySQL Server 5.6 and import UMLS data int
MS Graph API authentication example with Fast API
MS Graph API authentication example with Fast API What it is & does This is a simple python service/webapp, using FastAPI with server side rendering,
LynxKite: a complete graph data science platform for very large graphs and other datasets.
LynxKite is a complete graph data science platform for very large graphs and other datasets. It seamlessly combines the benefits of a friendly graphical interface and a powerful Python API.
Spaghetti: an open-source Python library for the analysis of network-based spatial data
pysal/spaghetti SPAtial GrapHs: nETworks, Topology, & Inference Spaghetti is an open-source Python library for the analysis of network-based spatial d
A visualization tool to show a TensorFlow's graph like TensorBoard
tfgraphviz tfgraphviz is a module to visualize a TensorFlow's data flow graph like TensorBoard using Graphviz. tfgraphviz enables to provide a visuali
An End-to-End Machine Learning Library to Optimize AUC (AUROC, AUPRC).
Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a
Build an Amazon SageMaker Pipeline to Transform Raw Texts to A Knowledge Graph
Build an Amazon SageMaker Pipeline to Transform Raw Texts to A Knowledge Graph This repository provides a pipeline to create a knowledge graph from ra
A websocket client for Source Filmmaker intended to trasmit scene and frame data to other applications.
SFM SOCK A websocket client for Source Filmmaker intended to trasmit scene and frame data to other applications. This software can be used to transmit
🐍PyNode Next allows you to easily create beautiful graph visualisations and animations
PyNode Next A complete rewrite of PyNode for the modern era. Up to five times faster than the original PyNode. PyNode Next allows you to easily create
Example Code Notebooks for Data Visualization in Python
This repository contains sample code scripts for creating awesome data visualizations from scratch using different python libraries (such as matplotli
Quick insights from Zoom meeting transcripts using Graph + NLP
Transcript Analysis - Graph + NLP This program extracts insights from Zoom Meeting Transcripts (.vtt) using TigerGraph and NLTK. In order to run this
Random Directed Acyclic Graph Generator
DAG_Generator Random Directed Acyclic Graph Generator verison1.0 简介 工作流通常由DAG(有向无环图)来定义,其中每个计算任务$T_i$由一个顶点(node,task,vertex)表示。同时,任务之间的每个数据或控制依赖性由一条加权
Code for "Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals," CoRL 2021.
Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals This repository contains code for "Multimodal trajectory prediction conditioned
Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"
Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching This repository is an official implementation of