Skip to content
StarGAN v2 - Official PyTorch Implementation
Branch: master
Clone or download
Latest commit 1092a12 Dec 27, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
assets Add files via upload Dec 6, 2019
.gitignore Initial commit Dec 4, 2019
LICENSE.txt Add license Dec 5, 2019
README.md Update README.md Dec 27, 2019

README.md

StarGAN v2 - Official PyTorch Implementation

This repository provides the official PyTorch implementation of the following paper:

StarGAN v2: Diverse Image Synthesis for Multiple Domains
Yunjey Choi*, Youngjung Uh*, Jaejun Yoo*, Jung-Woo Ha
Clova AI Research, NAVER Corp. (* indicates equal contribution)
https://arxiv.org/abs/1912.01865

Abstract: A good image-to-image translation model should learn a mapping between different visual domains while satisfying the following properties: 1) diversity of generated images and 2) scalability over multiple domains. Existing methods address either of the issues, having limited diversity or multiple models for all domains. We propose StarGAN v2, a single framework that tackles both and shows significantly improved results over the baselines. Experiments on CelebA-HQ and a new animal faces dataset (AFHQ) validate our superiority in terms of visual quality, diversity, and scalability. To better assess image-to-image translation models, we release AFHQ, high-quality animal faces with large inter- and intra-domain variations. The code, pretrained models, and dataset will be released for reproducibility.

Results

StarGAN v2 can transform a source image into an output image reflecting the style (e.g., hairstyle and makeup) of a given reference image. Additional high-quality videos can be found here.

License

The source code, pretrained models, and dataset will be available under Creative Commons BY-NC 4.0 license by NAVER Corporation. You can use, copy, tranform and build upon the material for non-commercial purposes as long as you give appropriate credit by citing our paper, and indicate if changes were made.

Installation

The code and usage examples will be updated soon. Please stay tuned.

Citation

If you find this work useful for your research, please cite our paper:

@article{choi2019starganv2,
  title={StarGAN v2: Diverse Image Synthesis for Multiple Domains},
  author={Yunjey Choi and Youngjung Uh and Jaejun Yoo and Jung-Woo Ha},
  journal={arXiv preprint arXiv:1912.01865},
  year={2019}
}
You can’t perform that action at this time.