generative-adversarial-network

Official Code for DragGAN (SIGGRAPH 2023)

Image-to-Image Translation in PyTorch

🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.

Synthesizing and manipulating 2048x1024 images with conditional GANs

Curated list of awesome GAN applications and demo

Compute FID scores with PyTorch.

Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement

Synthetic data generation for tabular data

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral

EdgeConnect: Structure Guided Image Inpainting using Edge Prediction, ICCV 2019 https://arxiv.org/abs/1901.00212

One-step image-to-image with Stable Diffusion turbo: sketch2image, day2night, and more

(ෆ`꒳´ෆ) A Survey on Text-to-Image Generation/Synthesis.

A large-scale face dataset for face parsing, recognition, generation and editing.

C++ Implementation of PyTorch Tutorials for Everyone

An AI for Music Generation

Implementation of GigaGAN, new SOTA GAN out of Adobe. Culmination of nearly a decade of research into GANs

State-of-the-art audio codec with 90x compression factor. Supports 44.1kHz, 24kHz, and 16kHz mono/stereo audio.

Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two

Collection of google colaboratory notebooks for fast and easy experiments

Synthetic data generators for tabular and time-series data

List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.

Conditional GAN for generating synthetic tabular data.

The official code repository for the second edition of the O'Reilly book Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play.

Unsupervised time series anomaly detection library

"Deep Generative Modeling": Introductory Examples

[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training

PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks