pix2pixhd

Synthesizing and manipulating 2048x1024 images with conditional GANs


Keywords
computer-graphics, computer-vision, deep-learning, deep-neural-networks, gan, generative-adversarial-network, image-to-image-translation, pix2pix, pytorch
License
BSD-3-Clause
Install
pip install pix2pixhd==1.0

Documentation





pix2pixHD

[Project] [Youtube] [Paper]

Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translation. It can be used for turning semantic label maps into photo-realistic images or synthesizing portraits from face label maps.

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
Ting-Chun Wang1, Ming-Yu Liu1, Jun-Yan Zhu2, Andrew Tao1, Jan Kautz1, Bryan Catanzaro1
1NVIDIA Corporation, 2UC Berkeley
In arxiv, 2017.

Release notice

The code is ready to publish but still under final approval process. It should be approved in a couple of days.
If you want to get notified once the code is released, please subscribe here.

Image-to-image translation at 2k/1k resolution

  • Our label-to-streetview results

- Interactive editing results

- Additional streetview results

  • Label-to-face and interactive editing results

  • Our editing interface

Citation

If you find this useful for your research, please use the following.

@article{wang2017highres,
  title={High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs},
  author={Ting-Chun Wang and Ming-Yu Liu and Jun-Yan Zhu and Andrew Tao and Jan Kautz and Bryan Catanzaro},
  journal={arXiv preprint arXiv:1711.11585},
  year={2017}
}