2943 Repositories
Python deep-curve-estimation Libraries
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
A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation
Paper Khoi Nguyen, Sinisa Todorovic "A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation", accepted to ICCV 2021 Our code is mai
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
SIR model parameter estimation using a novel algorithm for differentiated uniformization.
TenSIR Parameter estimation on epidemic data under the SIR model using a novel algorithm for differentiated uniformization of Markov transition rate m
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
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
Affine / perspective transformation in Pose Estimation with Tensorflow 2
Pose Transformation Affine / Perspective transformation in Pose Estimation with Tensorflow 2 Introduction 이 repo는 pose estimation을 연구하고 개발하는 데 도움이 되기
Fast syllable estimation library based on pattern matching.
Syllables: A fast syllable estimator for Python Syllables is a fast, simple syllable estimator for Python. It's intended for use in places where speed
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
MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice
Sampyl May 29, 2018: version 0.3 Sampyl is a package for sampling from probability distributions using MCMC methods. Similar to PyMC3 using theano to
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
Source code of the paper "Deep Learning of Latent Variable Models for Industrial Process Monitoring".
Source code of the paper "Deep Learning of Latent Variable Models for Industrial Process Monitoring".
All course materials for the Zero to Mastery Machine Learning and Data Science course.
Zero to Mastery Machine Learning Welcome! This repository contains all of the code, notebooks, images and other materials related to the Zero to Maste
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition"
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition" Pre-trained Deep Convo
A set of demo of deploying a Machine Learning Model in production using various methods
Machine Learning Model in Production This git is for those who have concern about serving your machine learning model to production. Overview The tuto
Quick tutorial on orchest.io that shows how to build multiple deep learning models on your data with a single line of code using python
Deep AutoViML Pipeline for orchest.io Quickstart Build Deep Learning models with a single line of code: deep_autoviml Deep AutoViML helps you build te
Deep Distributed Control of Port-Hamiltonian Systems
De(e)pendable Distributed Control of Port-Hamiltonian Systems (DeepDisCoPH) This repository is associated to the paper [1] and it contains: The full p
Deep Reinforcement Learning based autonomous navigation for quadcopters using PPO algorithm.
PPO-based Autonomous Navigation for Quadcopters This repository contains an implementation of Proximal Policy Optimization (PPO) for autonomous naviga
Repository for GNSS-based position estimation using a Deep Neural Network
Code repository accompanying our work on 'Improving GNSS Positioning using Neural Network-based Corrections'. In this paper, we present a Deep Neural
Example how to deploy deep learning model with aiohttp.
aiohttp-demos Demos for aiohttp project. Contents Imagetagger Deep Learning Image Classifier URL shortener Toxic Comments Classifier Moderator Slack B
Header-only library for using Keras models in C++.
frugally-deep Use Keras models in C++ with ease Table of contents Introduction Usage Performance Requirements and Installation FAQ Introduction Would
Streaming over lightweight data transformations
Description Data augmentation libarary for Deep Learning, which supports images, segmentation masks, labels and keypoints. Furthermore, SOLT is fast a
Semantic Edge Detection with Diverse Deep Supervision
Semantic Edge Detection with Diverse Deep Supervision This repository contains the code for our IJCV paper: "Semantic Edge Detection with Diverse Deep
PyTorch implementation of Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation Introduction This is a PyTorch
Marine debris detection with commercial satellite imagery and deep learning.
Marine debris detection with commercial satellite imagery and deep learning. Floating marine debris is a global pollution problem which threatens mari
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and so
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
LSTMs for Human Activity Recognition Human Activity Recognition (HAR) using smartphones dataset and an LSTM RNN. Classifying the type of movement amon
Simple and ready-to-use tutorials for TensorFlow
TensorFlow World To support maintaining and upgrading this project, please kindly consider Sponsoring the project developer. Any level of support is a
TensorFlow tutorials and best practices.
Effective TensorFlow 2 Table of Contents Part I: TensorFlow 2 Fundamentals TensorFlow 2 Basics Broadcasting the good and the ugly Take advantage of th
TensorFlow (Python API) implementation of Neural Style
neural-style-tf This is a TensorFlow implementation of several techniques described in the papers: Image Style Transfer Using Convolutional Neural Net
A deep learning network built with TensorFlow and Keras to classify gender and estimate age.
Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend
A Parameter-free Deep Embedded Clustering Method for Single-cell RNA-seq Data
A Parameter-free Deep Embedded Clustering Method for Single-cell RNA-seq Data Overview Clustering analysis is widely utilized in single-cell RNA-seque
A PyTorch based deep learning library for drug pair scoring.
Documentation | External Resources | Datasets | Examples ChemicalX is a deep learning library for drug-drug interaction, polypharmacy side effect and
Training deep models using anime, illustration images.
animeface deep models for anime images. Datasets anime-face-dataset Anime faces collected from Getchu.com. Based on Mckinsey666's dataset. 63.6K image
Functional deep learning
Pipeline abstractions for deep learning. Full documentation here: https://lf1-io.github.io/padl/ PADL: is a pipeline builder for PyTorch. may be used
ChainerRL is a deep reinforcement learning library built on top of Chainer.
ChainerRL and PFRL ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement al
Deep Reinforcement Learning for Keras.
Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml
[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation
SelectionGAN for Guided Image-to-Image Translation CVPR Paper | Extended Paper | Guided-I2I-Translation-Papers Citation If you use this code for your
AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation
AtlasNet [Project Page] [Paper] [Talk] AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation Thibault Groueix, Matthew Fisher, Vladimir
Open source repository for the code accompanying the paper 'PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations'.
PatchNets This is the official repository for the project "PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations". For details,
[ECCV'20] Convolutional Occupancy Networks
Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page | Blog Post This repository contains the implementation o
Volumetric Correspondence Networks for Optical Flow, NeurIPS 2019.
VCN: Volumetric correspondence networks for optical flow [project website] Requirements python 3.6 pytorch 1.1.0-1.3.0 pytorch correlation module (opt
Basics of 2D and 3D Human Pose Estimation.
Human Pose Estimation 101 If you want a slightly more rigorous tutorial and understand the basics of Human Pose Estimation and how the field has evolv
2D&3D human pose estimation
Human Pose Estimation Papers [CVPR 2016] - 201511 [IJCAI 2016] - 201602 Other Action Recognition with Joints-Pooled 3D Deep Convolutional Descriptors
The authors' implementation of Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations
Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations This is the authors' implementation of Unsupervised Adversarial Learning of
A simple baseline for 3d human pose estimation in PyTorch.
3d_pose_baseline_pytorch A PyTorch implementation of a simple baseline for 3d human pose estimation. You can check the original Tensorflow implementat
3D HourGlass Networks for Human Pose Estimation Through Videos
3D-HourGlass-Network 3D CNN Based Hourglass Network for Human Pose Estimation (3D Human Pose) from videos. This was my summer'18 research project. Dis
GAN-based 3D human pose estimation model for 3DV'17 paper
Tensorflow implementation for 3DV 2017 conference paper "Adversarially Parameterized Optimization for 3D Human Pose Estimation". @inproceedings{jack20
Efficient 3D human pose estimation in video using 2D keypoint trajectories
3D human pose estimation in video with temporal convolutions and semi-supervised training This is the implementation of the approach described in the
A simple baseline for 3d human pose estimation in tensorflow. Presented at ICCV 17.
3d-pose-baseline This is the code for the paper Julieta Martinez, Rayat Hossain, Javier Romero, James J. Little. A simple yet effective baseline for 3
Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
News! Aug 2020: v0.4.0 version of AlphaPose is released! Stronger tracking! Include whole body(face,hand,foot) keypoints! Colab now available. Dec 201
Training PyTorch models with differential privacy
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the cli
A deep learning network built with TensorFlow and Keras to classify gender and estimate age.
Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend
Computer vision - fun segmentation experience using classic and deep tools :)
Computer_Vision_Segmentation_Fun Segmentation of Images and Video. Tools: pytorch Models: Classic model - GrabCut Deep model - Deeplabv3_resnet101 Flo
[CoRL 21'] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo Lukas Koestler1* Nan Yang1,2*,† Niclas Zeller2,3 Daniel Cremers1
Yuno is context based search engine for anime.
Yuno yuno.mp4 Table of Contents Introduction Power Of Yuno Try Yuno How Yuno was created? References Introduction Yuno is a context based search engin
A Re-implementation of the paper "A Deep Learning Framework for Character Motion Synthesis and Editing"
What is This This is a simple re-implementation of the paper "A Deep Learning Framework for Character Motion Synthesis and Editing"(1). Only Sections
PyTorch implementation of Deep HDR Imaging via A Non-Local Network (TIP 2020).
NHDRRNet-PyTorch This is the PyTorch implementation of Deep HDR Imaging via A Non-Local Network (TIP 2020). 0. Differences between Original Paper and
Automatically remove the mosaics in images and videos, or add mosaics to them.
Automatically remove the mosaics in images and videos, or add mosaics to them.
BERT-based Financial Question Answering System
BERT-based Financial Question Answering System In this example, we use Jina, PyTorch, and Hugging Face transformers to build a production-ready BERT-b
Deep Learning segmentation suite designed for 2D microscopy image segmentation
Deep Learning segmentation suite dessigned for 2D microscopy image segmentation This repository provides researchers with a code to try different enco
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
[AAAI 2021] EMLight: Lighting Estimation via Spherical Distribution Approximation and [ICCV 2021] Sparse Needlets for Lighting Estimation with Spherical Transport Loss
EMLight: Lighting Estimation via Spherical Distribution Approximation (AAAI 2021) Update 12/2021: We release our Virtual Object Relighting (VOR) Datas
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
The source code is temporariy removed, as we are solving potential copyright and license issues with GRANSO (http://www.timmitchell.com/software/GRANS
Reference code for the paper "Cross-Camera Convolutional Color Constancy" (ICCV 2021)
Cross-Camera Convolutional Color Constancy, ICCV 2021 (Oral) Mahmoud Afifi1,2, Jonathan T. Barron2, Chloe LeGendre2, Yun-Ta Tsai2, and Francois Bleibe
Code for Deep Single-image Portrait Image Relighting
Deep Single-Image Portrait Relighting [Project Page] Hao Zhou, Sunil Hadap, Kalyan Sunkavalli, David W. Jacobs. In ICCV, 2019 Overview Test script for
Implementation of Nalbach et al. 2017 paper.
Deep Shading Convolutional Neural Networks for Screen-Space Shading Our project is based on Nalbach et al. 2017 paper. In this project, a set of buffe
🏃♀️ A curated list about human motion capture, analysis and synthesis.
Awesome Human Motion 🏃♀️ A curated list about human motion capture, analysis and synthesis. Contents Introduction Human Models Datasets Data Process
An end-to-end library for editing and rendering motion of 3D characters with deep learning [SIGGRAPH 2020]
Deep-motion-editing This library provides fundamental and advanced functions to work with 3D character animation in deep learning with Pytorch. The co
This repository contains the source code for the paper First Order Motion Model for Image Animation
!!! Check out our new paper and framework improved for articulated objects First Order Motion Model for Image Animation This repository contains the s
PyTorch implementation for our paper Learning Character-Agnostic Motion for Motion Retargeting in 2D, SIGGRAPH 2019
Learning Character-Agnostic Motion for Motion Retargeting in 2D We provide PyTorch implementation for our paper Learning Character-Agnostic Motion for
Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.
Codes-for-Algorithms Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.
Flow is a computational framework for deep RL and control experiments for traffic microsimulation.
Flow Flow is a computational framework for deep RL and control experiments for traffic microsimulation. See our website for more information on the ap
Malaya-Speech is a Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow.
Malaya-Speech is a Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow. Documentation Proper documentation is available at
Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention
Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz
DeLighT: Very Deep and Light-Weight Transformers
DeLighT: Very Deep and Light-weight Transformers This repository contains the source code of our work on building efficient sequence models: DeFINE (I
Fully featured implementation of Routing Transformer
Routing Transformer A fully featured implementation of Routing Transformer. The paper proposes using k-means to route similar queries / keys into the
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
ELECTRA Introduction ELECTRA is a method for self-supervised language representation learning. It can be used to pre-train transformer networks using
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac
Infrastructure template and Jupyter notebooks for running RoseTTAFold on AWS Batch.
AWS RoseTTAFold Infrastructure template and Jupyter notebooks for running RoseTTAFold on AWS Batch. Overview Proteins are large biomolecules that play
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
Class-balanced-loss-pytorch Pytorch implementation of the paper Class-Balanced Loss Based on Effective Number of Samples presented at CVPR'19. Yin Cui
Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning. CVPR 2018
Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning Tensorflow code and models for the paper: Large Scale Fine-Grained Categ
Code for paper "Learning to Reweight Examples for Robust Deep Learning"
learning-to-reweight-examples Code for paper Learning to Reweight Examples for Robust Deep Learning. [arxiv] Environment We tested the code on tensorf
PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning
Learning to Reweight Examples for Robust Deep Learning Unofficial PyTorch implementation of Learning to Reweight Examples for Robust Deep Learning. Th
A Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Training Data》
RangeLoss Pytorch This is a Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Trai
Deep learning for Engineers - Physics Informed Deep Learning
SciANN: Neural Networks for Scientific Computations SciANN is a Keras wrapper for scientific computations and physics-informed deep learning. New to S