Python Synthetic-gradients Resources

Dataset Distillation by Matching Training Trajectories Project Page | Paper This repo contains code for training expert trajectories and distilling sy

Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data (CVPR 2022) Potentials of primitive shapes f

SMDD-Synthetic-Face-Morphing-Attack-Detection-Development-dataset Official repository of the paper Privacy-friendly Synthetic Data for the Development

Conditional Gradients For The Approximately Vanishing Ideal Code for the paper: Wirth, E., and Pokutta, S. (2022). Conditional Gradients for the Appro

Learning Synthetic Environments and Reward Networks for Reinforcement Learning We explore meta-learning agent-agnostic neural Synthetic Environments (

Learning to Predict Gradients for Semi-Supervised Continual Learning Code for project: "Learning to Predict Gradients for Semi-Supervised Continual Le

Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation Prerequisites This repo is built upon a local copy of transfo

Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are statistical models that allow these properties to be simulated (Joe 2014). As such, copula generated data have shown potential to improve the generalization of machine learning (ML) emulators (Meyer et al. 2021) or anonymize real-data datasets (Patki et al. 2016).

LSF-SAC Pytorch implementations of the paper Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy G

HOW TO USE THIS PROJECT A Review of Deep Learning Techniques for Markerless Human Motion on Synthetic Datasets Based on DeepLabCut toolbox, we run wit

A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)

TimeSynth Multipurpose Library for Synthetic Time Series Please cite as: J. R. Maat, A. Malali, and P. Protopapas, “TimeSynth: A Multipurpose Library

OCR-Pipeline-with-Keras The keras-ocr package generally consists of two parts: a Detector and a Recognizer: Detector is responsible for creating bound

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

AdaBelief Optimizer NeurIPS 2020 Spotlight, trains fast as Adam, generalizes well as SGD, and is stable to train GANs. Release of package We have rele

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Above is an adversarial example: the slightly pert

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

timeseries-generator This repository consists of a python packages that generates synthetic time series dataset in a generic way (under /timeseries_ge

Introduction UnrealText is a project that synthesizes scene text images using 3D graphics engine. This repository accompanies our paper: UnrealText: S

Learning from Synthetic Humans (SURREAL) Gül Varol, Javier Romero, Xavier Martin, Naureen Mahmood, Michael J. Black, Ivan Laptev and Cordelia Schmid,

Random database/dataframe generator Authored and maintained by Dr. Tirthajyoti Sarkar, Fremont, USA Introduction Often, beginners in SQL or data scien

An Open Source Project from the Data to AI Lab, at MIT Website: https://sdv.dev Documentation: https://sdv.dev/SDV User Guides Developer Guides Github

Voxelized 3D Feature Aggregation for Multiview Detection [arXiv] Multiview 3D object detection on MultiviewC dataset through VFA. Introduction We prop

pytorch_clip_guided_loss: Pytorch implementation of the CLIP guided loss for Text-To-Image, Image-To-Image, or Image-To-Text generation. A simple libr

MediumVC MediumVC is an utterance-level method towards any-to-any VC. Before that, we propose SingleVC to perform A2O tasks(Xi → Ŷi) , Xi means utter

Continuous Control With Ensemble Deep Deterministic Policy Gradients This repository is the official implementation of Continuous Control With Ensembl

Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L

GradAttack is a Python library for easy evaluation of privacy risks in public gradients in Federated Learning, as well as corresponding mitigation strategies.

Federated_Learning This repo provides a federated learning framework that allows to carry out backdoor attacks under varying conditions. This is a ker

SynthText Code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Ved

Traditional Chinese Text Recognition Dataset: Synthetic Dataset and Labeled Data Authors: Yi-Chang Chen, Yu-Chuan Chang, Yen-Cheng Chang and Yi-Ren Ye

BlenderProc2 A procedural Blender pipeline for photorealistic rendering. Documentation | Tutorials | Examples | ArXiv paper | Workshop paper Features

An Open Source Project from the Data to AI Lab, at MIT Metrics for Synthetic Data Generation Projects Website: https://sdv.dev Documentation: https://

Synthetic Control Methods A Python package for causal inference using synthetic controls This Python package implements a class of approaches to estim

A python package to manage the stored receiver-side Strain Green's Tensor (SGT) database of 3D background models and able to generate Green's function and synthetic waveform

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

Simulated+Unsupervised (S+U) Learning in TensorFlow TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial T

AOS: Airborne Optical Sectioning Airborne Optical Sectioning (AOS) is a wide synthetic-aperture imaging technique that employs manned or unmanned airc

Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness Code for Paper "Imbalanced Gradients: A Subtle Cause of Overestimated Adv

Principled S2R Dehazing This repository contains the official implementation for PSD Framework introduced in the following paper: PSD: Principled Synt

The Hypersim Dataset For many fundamental scene understanding tasks, it is difficult or impossible to obtain per-pixel ground truth labels from real i

Can we learn gradients by Hamiltonian Neural Networks? This project was carried out as part of the Optimization for Machine Learning course (CS-439) a

Synthetic-Data-Replica-for-Healthcare Description What is this? A tailored hands-on tutorial showing how to use Python to create synthetic data replic

Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples This repository is the official implementation of paper [Qimera: Data-free Q

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

DECAF (DEbiasing CAusal Fairness) Code Author: Trent Kyono This repository contains the code used for the "DECAF: Generating Fair Synthetic Data Using

Estimating Example Difficulty using Variance of Gradients This repository contains source code necessary to reproduce some of the main results in the

LDNet Author: Wen-Chin Huang (Nagoya University) Email: [email protected] This is the official implementation of the paper "LDNet

Retailer's Sale Data Simulation Retail-Sim is python package to easily create synthetic dataset of retaile store. Simulation Model Simulator consists

Conditional Smiles! (SmileCVAE) About Implementation of AE, VAE and CVAE. Trained CVAE on faces from UTKFace Dataset. Using an encoding of the Smile-s

SegSwap Pytorch implementation of paper "Learning Co-segmentation by Segment Swapping for Retrieval and Discovery" [PDF] [Project page] If our project

Join us on What is Synthetic Data? Synthetic data is artificially generated data that is not collected from real world events. It replicates the stati

LDNet Author: Wen-Chin Huang (Nagoya University) Email: [email protected] This is the official implementation of the paper "LDNet

Official PyTorch implementation of "Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection" This is the implementation of the paper "Syn

Multiview Orthographic Feature Transformation for 3D Object Detection Multiview 3D object detection on MultiviewC dataset through moft3d. Introduction

SynNet This repo contains the code and analysis scripts for our amortized approach to synthetic tree generation using neural networks. Our model can s

A synthetic dataset for object detection of UAVs This repository contains a synthetic datasets accompanying the paper Sim2Air - Synthetic aerial datas

Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification Suncheng Xiang Shanghai Jiao Tong University Over

This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.

The Face Synthetics dataset Face Synthetics dataset is a collection of diverse synthetic face images with ground truth labels. It was introduced in ou

MediumVC MediumVC is an utterance-level method towards any-to-any VC. Before that, we propose SingleVC to perform A2O tasks(Xi → Ŷi) , Xi means utter

Code repository for Invariant Risk Minimization Source code for the paper: @article{InvariantRiskMinimization, title={Invariant Risk Minimization}

functorch is a prototype of JAX-like composable function transforms for PyTorch.

Discretized Integrated Gradients for Explaining Language Models (EMNLP 2021) Overview of paths used in DIG and IG. w is the word being attributed. The

Real2CAD-3DV Shape Matching of Real 3D Object Data to Synthetic 3D CADs (3DV project @ ETHZ) Group Member: Yue Pan, Yuanwen Yue, Bingxin Ke, Yujie He

Real-ESRGAN Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data Ported from https://github.com/xinntao/Real-ESRGAN Depend

About This repository provides data and code for the paper: Scalable Data Annotation Pipeline for High-Quality Large Speech Datasets Development (subm

disclaimer: this code is modified from pytorch-tutorial Image classification with synthetic gradient in Pytorch I implement the Decoupled Neural Inter

pytorch-a2c-ppo-acktr Update (April 12th, 2021) PPO is great, but Soft Actor Critic can be better for many continuous control tasks. Please check out

Genalog is an open source, cross-platform python package allowing generation of synthetic document images with custom degradations and text alignment capabilities.

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan

🐯 SynthTIGER: Synthetic Text Image GEneratoR Official implementation of SynthTIGER | Paper | Datasets Moonbin Yim1, Yoonsik Kim1, Han-cheol Cho1, Sun

SynLiDAR dataset: Learning From Synthetic LiDAR Sequential Point Cloud This is official repository of the SynLiDAR dataset. For technical details, ple

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan

IAug_CDNet Official Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images. Overview We propose a

SDL is the project that synthesizes document images. It facilitates multiple-level labeling on document images and can generate in multiple languages.

This is the dataset and code release of the OpenRooms Dataset.

Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning Official PyTorch implementation of "Proxy Synthesis: Learning with Synthetic

MetaAdaptRank This repository provides the implementation of meta-learning to reweight synthetic weak supervision data described in the paper Few-Shot

SURREACT: Synthetic Humans for Action Recognition from Unseen Viewpoints Gül Varol, Ivan Laptev and Cordelia Schmid, Andrew Zisserman, Synthetic Human

Reinforcement Learning (PyTorch) 🤖 + 🍰 = ❤️ This repo will contain PyTorch implementation of various fundamental RL algorithms. It's aimed at making

SharinGAN Official repo for the work titled "SharinGAN: Combining Synthetic and Real Data for Unsupervised GeometryEstimation" The official project we

Multi-Agent-Deep-Deterministic-Policy-Gradients A Pytorch implementation of the multi agent deep deterministic policy gradients(MADDPG) algorithm This

higher is a library providing support for higher-order optimization, e.g. through unrolled first-order optimization loops, of "meta" aspects of these

awesome-SynthText A curated list of awesome synthetic data for text location and recognition and OCR datasets. Text location SynthText SynthText_Chine

TextRecognitionDataGenerator A synthetic data generator for text recognition What is it for? Generating text image samples to train an OCR software. N

PGPElib A mini library for Policy Gradients with Parameter-based Exploration [1] and friends. This library serves as a clean re-implementation of the

Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O

zpy: Synthetic data in Blender. Website • Install • Docs • Examples • CLI • Contribute • Licence Abstract Collecting, labeling, and cleaning data for

Learning from Synthetic Shadows for Shadow Detection and Removal (IEEE TCSVT 2020) Overview This repo is for the paper "Learning from Synthetic Shadow

Mimesis - Fake Data Generator Description Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes

Mimesis - Fake Data Generator Description Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes