3207 Repositories
Python awesome-generative-deep-art Libraries
Ladder network is a deep learning algorithm that combines supervised and unsupervised learning
This repository contains source code for the experiments in a paper titled Semi-Supervised Learning with Ladder Networks by A Rasmus, H Valpola, M Hon
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations The code of: Weakly Supervised Learning of Instance Segmentation with I
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018
Adversarial Learning for Semi-supervised Semantic Segmentation This repo is the pytorch implementation of the following paper: Adversarial Learning fo
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
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR 2018).
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR2018) By Zilong Huang, Xinggang Wang, Jiasi Wang, Wenyu Liu and J
Weakly-supervised object detection.
Wetectron Wetectron is a software system that implements state-of-the-art weakly-supervised object detection algorithms. Project CVPR'20, ECCV'20 | Pa
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
Deep SAD: A Method for Deep Semi-Supervised Anomaly Detection This repository provides a PyTorch implementation of the Deep SAD method presented in ou
Datasets for new state-of-the-art challenge in disentanglement learning
High resolution disentanglement datasets This repository contains the Falcor3D and Isaac3D datasets, which present a state-of-the-art challenge for co
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1
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
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
Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
Semi-supervised Deep Kernel Learning This is the code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data
Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters.
Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters. Overview This project is a Torch implementation for our CVPR 2016 paper
Decensoring Hentai with Deep Neural Networks. Formerly named DeepMindBreak.
DeepCreamPy Decensoring Hentai with Deep Neural Networks. Formerly named DeepMindBreak. A deep learning-based tool to automatically replace censored a
Remote sensing change detection using PaddlePaddle
Change Detection Laboratory Developing and benchmarking deep learning-based remo
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
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
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
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
Introduction QRec is a Python framework for recommender systems (Supported by Python 3.7.4 and Tensorflow 1.14+) in which a number of influential and
ncnn is a high-performance neural network inference framework optimized for the mobile platform
ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme
Deep Hedging Demo - An Example of Using Machine Learning for Derivative Pricing.
Deep Hedging Demo Pricing Derivatives using Machine Learning 1) Jupyter version: Run ./colab/deep_hedging_colab.ipynb on Colab. 2) Gui version: Run py
Minimal implementation and experiments of "No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging".
No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging Minimal implementation and experiments of "No-Transaction Band N
PyTorch-based framework for Deep Hedging
PFHedge: Deep Hedging in PyTorch PFHedge is a PyTorch-based framework for Deep Hedging. PFHedge Documentation Neural Network Architecture for Efficien
Official implementation of CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21
CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21 For more information, check out the paper on [arXiv]. Training with different
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation Where we are ? 12.27 目前和原论文仍有1%左右得差距,但已经力压很多SOTA了 ckpt__448_epoch_25.pth mIoU
A curated list of awesome Model-Based RL resources
Awesome Model-Based Reinforcement Learning This is a collection of research papers for model-based reinforcement learning (mbrl). And the repository w
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥
ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage
Retrieve and analysis data from SDSS (Sloan Digital Sky Survey)
Author: Behrouz Safari License: MIT sdss A python package for retrieving and analysing data from SDSS (Sloan Digital Sky Survey) Installation Install
Python implementation of O-OFDMNet, a deep learning-based optical OFDM system,
O-OFDMNet This includes Python implementation of O-OFDMNet, a deep learning-based optical OFDM system, which uses neural networks for signal processin
Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch
CutPaste CutPaste: image from paper Unofficial implementation of Google's "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization"
Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods."
pv_predict_unet-lstm Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods." IEEE Transactions
Deep Semisupervised Multiview Learning With Increasing Views (IEEE TCYB 2021, PyTorch Code)
Deep Semisupervised Multiview Learning With Increasing Views (ISVN, IEEE TCYB) Peng Hu, Xi Peng, Hongyuan Zhu, Liangli Zhen, Jie Lin, Huaibai Yan, Dez
Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer axriv: http://arxiv.org/abs/2112.13513
MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis This is the official page of the MSHT with its experimental script and records. We de
Official repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION.
IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION This is the official repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSU
For storing the complete exploration of Visual Question Answering for our B.Tech Project
Multi-Image vqa @authors: Akhilesh, Janhavi, Harsh Paper summary, Ideas tried and their corresponding results: on wiki Other discussions: on discussio
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
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
[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
Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
Official PyTorch implementation of the paper: "Self-Supervised Relational Reasoning for Representation Learning" (2020), Patacchiola, M., and Storkey,
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
SfMLearner This codebase implements the system described in the paper: Unsupervised Learning of Depth and Ego-Motion from Video Tinghui Zhou, Matthew
Geometry-Aware Learning of Maps for Camera Localization (CVPR2018)
Geometry-Aware Learning of Maps for Camera Localization This is the PyTorch implementation of our CVPR 2018 paper "Geometry-Aware Learning of Maps for
gcrypter: an encryption algorithm based on bytes and their correspondent numbers to encode strings
gcrypter: an encryption algorithm based on bytes and their correspondent numbers to encode strings
Deep Learning Training Scripts With Python
Deep Learning Training Scripts DNN Frameworks Caffe PyTorch Tensorflow CNN Models VGG ResNet DenseNet Inception Language Modeling GatedCNN-LM Attentio
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p
Indonesian Car License Plate Character Recognition using Tensorflow, Keras and OpenCV.
Monopol Indonesian Car License Plate (Indonesia Mobil Nomor Polisi) Character Recognition using Tensorflow, Keras and OpenCV. Background This applicat
🚀Clone a voice in 5 seconds to generate arbitrary speech in real-time
English | 中文 Features 🌍 Chinese supported mandarin and tested with multiple datasets: aidatatang_200zh, magicdata, aishell3, data_aishell, and etc. ?
A deep learning model for style-specific music generation.
DeepJ: A model for style-specific music generation https://arxiv.org/abs/1801.00887 Abstract Recent advances in deep neural networks have enabled algo
Fast, DB Backed pretrained word embeddings for natural language processing.
Embeddings Embeddings is a python package that provides pretrained word embeddings for natural language processing and machine learning. Instead of lo
PyTorch Implementation for Deep Metric Learning Pipelines
Easily Extendable Basic Deep Metric Learning Pipeline Karsten Roth ([email protected]), Biagio Brattoli ([email protected]) When using thi
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
News December 27: v1.1.0 New loss functions: CentroidTripletLoss and VICRegLoss Mean reciprocal rank + per-class accuracies See the release notes Than
Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.
The Ultimate PyTorch Source-Build Template Translations: 한국어 TL;DR PyTorch built from source can be x4 faster than a naïve PyTorch install. This repos
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
2021: A Year Full of Amazing AI papers- A Review 📌 A curated list of the latest breakthroughs in AI by release date with a clear video explanation, l
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size.
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size. The hub data layout enables rapid transformations and streaming of data while training models at scale. Hub is used by Google, Waymo, Red Cross, Oxford University, and Omdena.
Pytorch based library to rank predicted bounding boxes using text/image user's prompts.
pytorch_clip_bbox: Implementation of the CLIP guided bbox ranking for Object Detection. Pytorch based library to rank predicted bounding boxes using t
ONNX Command-Line Toolbox
ONNX Command Line Toolbox Aims to improve your experience of investigating ONNX models. Use it like onnx infershape /path/to/model.onnx. (See the usag
Deploy recommendation engines with Edge Computing
RecoEdge: Bringing Recommendations to the Edge A one stop solution to build your recommendation models, train them and, deploy them in a privacy prese
Tensorflow implementation for "Improved Transformer for High-Resolution GANs" (NeurIPS 2021).
HiT-GAN Official TensorFlow Implementation HiT-GAN presents a Transformer-based generator that is trained based on Generative Adversarial Networks (GA
High accurate tool for automatic faces detection with landmarks
faces_detanator High accurate tool for automatic faces detection with landmarks. The library is based on public detectors with high accuracy (TinaFace
PyTorch Implementation of PIXOR: Real-time 3D Object Detection from Point Clouds
PIXOR: Real-time 3D Object Detection from Point Clouds This is a custom implementation of the paper from Uber ATG using PyTorch 1.0. It represents the
RCDNet: A Model-driven Deep Neural Network for Single Image Rain Removal (CVPR2020)
RCDNet: A Model-driven Deep Neural Network for Single Image Rain Removal (CVPR2020) Hong Wang, Qi Xie, Qian Zhao, and Deyu Meng [PDF] [Supplementary M
BisQue is a web-based platform designed to provide researchers with organizational and quantitative analysis tools for 5D image data. Users can extend BisQue by implementing containerized ML workflows.
Overview BisQue is a web-based platform specifically designed to provide researchers with organizational and quantitative analysis tools for up to 5D
Displays Christmas-themed ASCII art
Christmas Color Scripts Displays Christmas-themed ASCII art. This was mainly inspired by DistroTube's Shell Color Scripts Screenshots ASCII Shadow Tex
A minimal implementation of face-detection models using flask, gunicorn, nginx, docker, and docker-compose
Face-Detection-flask-gunicorn-nginx-docker This is a simple implementation of dockerized face-detection restful-API implemented with flask, Nginx, and
A collection of awesome sqlite tools, scripts, books, etc
Awesome Series @ Planet Open Data World (Countries, Cities, Codes, ...) • Football (Clubs, Players, Stadiums, ...) • SQLite (Tools, Books, Schemas, ..
Neptune client library - integrate your Python scripts with Neptune
Lightweight experiment tracking tool for AI/ML individuals and teams. Fits any workflow. Neptune is a lightweight experiment logging/tracking tool tha
A Lightweight NLP Data Loader for All Deep Learning Frameworks in Python
LineFlow: Framework-Agnostic NLP Data Loader in Python LineFlow is a simple text dataset loader for NLP deep learning tasks. LineFlow was designed to
Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.
Welcome to Spokestack Python! This library is intended for developing voice interfaces in Python. This can include anything from Raspberry Pi applicat
Official repository of the AAAI'2022 paper "Contrast and Generation Make BART a Good Dialogue Emotion Recognizer"
CoG-BART Contrast and Generation Make BART a Good Dialogue Emotion Recognizer Quick Start: To run the model on test sets of four datasets, Download th
An self sufficient AI that crawls the web to learn how to generate art from keywords
Roxx-IO - The Smart Artist AI! TO DO / IDEAS Implement Web-Scraping Functionality Figure out a less annoying (and an off button for it) text to speech
[PNAS2021] The neural architecture of language: Integrative modeling converges on predictive processing
The neural architecture of language: Integrative modeling converges on predictive processing Code accompanying the paper The neural architecture of la
A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation.
Continuous Wasserstein-2 Benchmark This is the official Python implementation of the NeurIPS 2021 paper Do Neural Optimal Transport Solvers Work? A Co
Source code of SIGIR2021 Paper 'One Chatbot Per Person: Creating Personalized Chatbots based on Implicit Profiles'
DHAP Source code of SIGIR2021 Long Paper: One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles . Preinstallation Fir
Weakly Supervised End-to-End Learning (NeurIPS 2021)
WeaSEL: Weakly Supervised End-to-end Learning This is a PyTorch-Lightning-based framework, based on our End-to-End Weak Supervision paper (NeurIPS 202
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
This library is a location of the LegacyLogger for PyTorch Lightning.
neptune-contrib Documentation See neptune-contrib documentation site Installation Get prerequisites python versions 3.5.6/3.6 are supported Install li
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
This is a repository to learn and get more computer vision skills, make robotics projects integrating the computer vision as a perception tool and create a lot of awesome advanced controllers for the robots of the future.
This is a repository to learn and get more computer vision skills, make robotics projects integrating the computer vision as a perception tool and create a lot of awesome advanced controllers for the robots of the future.
ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python)
ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python) 日本語は以下に続きます (Japanese follows) English: This book is written in Japanese and primaril
Final project code: Implementing BicycleGAN, for CIS680 FA21 at University of Pennsylvania
680 Final Project: BicycleGAN Haoran Tang Instructions 1. Training To train the network, please run train.py. Change hyper-parameters and folder paths
Final project code: Implementing MAE with downscaled encoders and datasets, for ESE546 FA21 at University of Pennsylvania
546 Final Project: Masked Autoencoder Haoran Tang, Qirui Wu 1. Training To train the network, please run mae_pretraining.py. Please modify folder path
Latte: Cross-framework Python Package for Evaluation of Latent-based Generative Models
Cross-framework Python Package for Evaluation of Latent-based Generative Models Latte Latte (for LATent Tensor Evaluation) is a cross-framework Python
Deep motion transfer
animation-with-keypoint-mask Paper The right most square is the final result. Softmax mask (circles): \ Heatmap mask: \ conda env create -f environmen
Official Implementation of VAT
Semantic correspondence Few-shot segmentation Cost Aggregation Is All You Need for Few-Shot Segmentation For more information, check out project [Proj
Super Resolution for images using deep learning.
Neural Enhance Example #1 — Old Station: view comparison in 24-bit HD, original photo CC-BY-SA @siv-athens. As seen on TV! What if you could increase
Pytorch implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion"
MOSNet pytorch implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion" https://arxiv.org/abs/1904.08352 Dependency L
Some bravo or inspiring research works on the topic of curriculum learning.
Awesome Curriculum Learning Some bravo or inspiring research works on the topic of curriculum learning. A curated list of awesome Curriculum Learning
TeachMyAgent is a testbed platform for Automatic Curriculum Learning methods in Deep RL.
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL Paper Website Documentation TeachMyAgent is a testbed platform for Automatic Cu
Pytorch implementation for "Open Compound Domain Adaptation" (CVPR 2020 ORAL)
Open Compound Domain Adaptation [Project] [Paper] [Demo] [Blog] Overview Open Compound Domain Adaptation (OCDA) is the author's re-implementation of t
Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks This is the code for the paper: MentorNet: Learning Data-Driven Curriculum fo
Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes, ICCV 2017
AdaptationSeg This is the Python reference implementation of AdaptionSeg proposed in "Curriculum Domain Adaptation for Semantic Segmentation of Urban
Download your Spotify playlists and songs along with album art and metadata
spotDL Download your Spotify playlists and songs along with album art and metadata The fastest, easiest, and most accurate command-line music download
Flashback is an awesome, retro IRC based app built using Django
Flashback Flashback is an awesome, retro IRC based app built using Django (and the Django Rest Framework) for the backend as well as React for the fro
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences an
Keras implementation of PersonLab for Multi-Person Pose Estimation and Instance Segmentation.
PersonLab This is a Keras implementation of PersonLab for Multi-Person Pose Estimation and Instance Segmentation. The model predicts heatmaps and vari
PyTorch implementation of Super SloMo by Jiang et al.
Super-SloMo PyTorch implementation of "Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation" by Jiang H., Sun
A Deep Learning Framework for Neural Derivative Hedging
NNHedge NNHedge is a PyTorch based framework for Neural Derivative Hedging. The following repository was implemented to ease the experiments of our pa
StyleSwin: Transformer-based GAN for High-resolution Image Generation
StyleSwin This repo is the official implementation of "StyleSwin: Transformer-based GAN for High-resolution Image Generation". By Bowen Zhang, Shuyang
Official repository for "Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring".
RNN-MBP Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring (AAAI-2022) by Chao Zhu, Hang Dong, Jinshan Pan