Python Scene-graph-generation Resources

SG2HOI This repository is for our paper Exploiting Scene Graphs for Human-Object Interaction Detection accepted by ICCV 2021. Installation Pytorch 1.7

Voxel-based Network for Shape Completion by Leveraging Edge Generation This is the PyTorch implementation for the paper "Voxel-based Network for Shape

Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose

Spatio-Temporal Dynamic Inference Network for Group Activity Recognition The source codes for ICCV2021 Paper: Spatio-Temporal Dynamic Inference Networ

Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr

Documentation | Paper [JMLR] | Tutorials | Benchmarks | Examples DIG: Dive into Graphs is a turnkey library for graph deep learning research. Why DIG?

About visualapplets.py The Basler AG company provides a TCL scripting engine to automatize the creation of VisualApplets designs (a former Silicon Sof

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

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

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

Knowledge Repo The Knowledge Repo project is focused on facilitating the sharing of knowledge between data scientists and other technical roles using

GPT2-Chinese Description Chinese version of GPT2 training code, using BERT tokenizer or BPE tokenizer. It is based on the extremely awesome repository

Multi-level Disentanglement Graph Neural Network (MD-GNN) This is a PyTorch implementation of the MD-GNN, and the code includes the following modules:

✔️ 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

Help-Me-Read A web application created with Flask + BootStrap + HuggingFace 🤗 to generate summary and question-answer from given input text. It uses

Music_Gen_Streamlit "Music Generation using Neural Networks" Streamlit App TO DO: Make a run_app.sh Introduction [~5 min] (Sohaib) Team Member names/i

mask-uncertainty-in-HSI This repository contains the testing code and pre-trained models for the paper Calibrated Hyperspectral Image Reconstruction v

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 This repository implements the SAFL in pytorch. Installation conda env create -f environm

SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement This repository implements the approach described in SporeAgent: Reinforced

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

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

lbs-data Motivation Location data is collected from the public by private firms via mobile devices. Can this data also be used to serve the public goo

Splicing ViT Features for Semantic Appearance Transfer [Project Page] Splice is a method for semantic appearance transfer, as described in Splicing Vi

AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation AniGAN: Style-Guided Generative Adversarial Networks for U

Contrastive Unpaired Translation (CUT) video (1m) | video (10m) | website | paper We provide our PyTorch implementation of unpaired image-to-image tra

TSIT: A Simple and Versatile Framework for Image-to-Image Translation This repository provides the official PyTorch implementation for the following p

Contents XingGAN or CrossingGAN Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Evaluation Acknowl

Diverse Image Generation via Self-Conditioned GANs Project | Paper Diverse Image Generation via Self-Conditioned GANs Steven Liu, Tongzhou Wang, David

SEAN: Image Synthesis with Semantic Region-Adaptive Normalization (CVPR 2020 Oral) Figure: Face image editing controlled via style images and segmenta

STEFANN: Scene Text Editor using Font Adaptive Neural Network @ The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020.

Future urban scene generation through vehicle synthesis This repository contains Pytorch code for the ICPR2020 paper "Future Urban Scene Generation Th

AsymmetricGAN for Image-to-Image Translation AsymmetricGAN Framework for Multi-Domain Image-to-Image Translation AsymmetricGAN Framework for Hand Gest

Contents Cycle-In-Cycle GANs Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Acknowledgments Relat

AttentionGAN-v2 for Unpaired Image-to-Image Translation AttentionGAN-v2 Framework The proposed generator learns both foreground and background attenti

Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle

Scan2Cap: Context-aware Dense Captioning in RGB-D Scans Introduction We introduce the task of dense captioning in 3D scans from commodity RGB-D sensor

Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs This repository contains PyTorch implementation of our pa

M²: Meshed-Memory Transformer This repository contains the reference code for the paper Meshed-Memory Transformer for Image Captioning (CVPR 2020). Pl

awesome image-to-image translation A collection of resources on image-to-image translation. Contributing If you think I have missed out on something (

VCM EE1.2 P-layer feature map anchor generation 137th MPEG-VCM

SA-tensorflow Tensorflow implementation of soft-attention mechanism for video caption generation. An example of soft-attention mechanism. The attentio

Introduction This neural system for image captioning is roughly based on the paper "Show, Attend and Tell: Neural Image Caption Generation with Visual

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio

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

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 Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers

VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion (Interspeech

Total number of Spanning Trees in a Graph This is a python script just written f

Weakly- and Semi-Supervised Panoptic Segmentation by Qizhu Li*, Anurag Arnab*, Philip H.S. Torr This repository demonstrates the weakly supervised gro

Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1

Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering

Confidence-based Graph Convolutional Networks for Semi-Supervised Learning Source code for AISTATS 2019 paper: Confidence-based Graph Convolutional Ne

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear

G3NN This repo provides a pytorch implementation for the 4 instantiations of the flexible generative framework as described in the following paper: A

Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*

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. Before 😐 😶 😒 After ?

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N

GRACE The official PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE). For a thorough resource collection of self-superv

GMI (Graphical Mutual Information) Graph Representation Learning via Graphical Mutual Information Maximization (Peng Z, Huang W, Luo M, et al., WWW 20

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 Our article is PT-DGNN and the code is modified based on GPT-GNN Requirements python 3.6 Ubuntu 18.04.5 L

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 (DMGI) Overview Nodes in a multiplex network are connected by multiple types of relations. However

Heterogeneous-Deep-Graph-Infomax Parameter Setting: HDGI-A: Node-level dimension: 16 Attention head: 4 Semantic-level attention vector: 8 learning rat

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-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu

A bulk html pdf generator. This application can generate PDFs in bulk by using just one click. Screenshots Requirements 🧱 Your system must have the f

Welcome to SnakeMD SnakeMD is your ticket to generating Markdown in Python. To prove it to you, we've generated this entire README using SnakeMD. See

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

PyMeasure scientific package PyMeasure makes scientific measurements easy to set up and run. The package contains a repository of instrument classes a

GDSHelpers GDSHelpers in an open-source package for automatized pattern generation for nano-structuring. It allows exporting the pattern in the GDSII-

СоАвтор СоАвтор – платформа и открытый набор инструментов для редакций и журналистов-фрилансеров, который призван сделать процесс создания контента ма

Catbird is an open source paraphrase generation toolkit based on PyTorch. Quick Start Requirements and Installation The project is based on PyTorch 1.

pv_predict_unet-lstm Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods." IEEE Transactions

Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm

NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).

SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe

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

Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training

SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks

G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B

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

Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa

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" Please refer to htt

Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.

DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program

Implementation for the papers: Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs, Nurendra Choudhary, Nikhil Rao,

[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) Competition URL: https://tbrain.t

Knowledge Bridging for Empathetic Dialogue Generation This is the official implementation for paper Knowledge Bridging for Empathetic Dialogue Generat

SAG-DTA The code is the implementation for the paper 'SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network'. Requirements py

DeepJ: A model for style-specific music generation https://arxiv.org/abs/1801.00887 Abstract Recent advances in deep neural networks have enabled algo

Cross Domain Facial Expression Recognition Benchmark Implementation of papers: Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchm