Synthetic Data Generation

115 papers with code • 1 benchmarks • 3 datasets

The generation of tabular data by any means possible.


Use these libraries to find Synthetic Data Generation models and implementations

Most implemented papers

Wasserstein GAN

labmlai/annotated_deep_learning_paper_implementations 26 Jan 2017

We introduce a new algorithm named WGAN, an alternative to traditional GAN training.

Improved Training of Wasserstein GANs

igul222/improved_wgan_training NeurIPS 2017

Generative Adversarial Networks (GANs) are powerful generative models, but suffer from training instability.

Synthetic QA Corpora Generation with Roundtrip Consistency

patil-suraj/question_generation ACL 2019

We introduce a novel method of generating synthetic question answering corpora by combining models of question generation and answer extraction, and by filtering the results to ensure roundtrip consistency.

Generating Multidimensional Clusters With Support Lines

clugen/CluGen.jl 24 Jan 2023

Synthetic data is essential for assessing clustering techniques, complementing and extending real data, and allowing for a more complete coverage of a given problem's space.

HP-GAN: Probabilistic 3D human motion prediction via GAN

ebarsoum/hpgan 27 Nov 2017

Our model, which we call HP-GAN, learns a probability density function of future human poses conditioned on previous poses.

Burst Denoising with Kernel Prediction Networks

google/burst-denoising CVPR 2018

We present a technique for jointly denoising bursts of images taken from a handheld camera.

Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions

fjxmlzn/DoppelGANger 30 Sep 2019

By shedding light on the promise and challenges, we hope our work can rekindle the conversation on workflows for data sharing.

CrossLoc: Scalable Aerial Localization Assisted by Multimodal Synthetic Data

topo-epfl/crossloc CVPR 2022

We present a visual localization system that learns to estimate camera poses in the real world with the help of synthetic data.

Delving into High-Quality Synthetic Face Occlusion Segmentation Datasets

kennyvoo/face_occlusion_generation 12 May 2022

This paper performs comprehensive analysis on datasets for occlusion-aware face segmentation, a task that is crucial for many downstream applications.

Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions

juangamella/sempler 27 Nov 2022

We leverage this procedure and evaluate the performance of GnIES on synthetic, real, and semi-synthetic data sets.