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Mask-Guided Portrait Editing with Conditional GANs

This is an official pytorch implementation of "Mask-Guided Portrait Editing with Conditional GANs"(CVPR2019). The major contributors of this repository include Shuyang Gu, Jianmin Bao, Hao Yang, Dong Chen, Fang Wen, Lu Yuan at Microsoft Research.

Introduction

Mask-Guided Portrait Editing is a novel technology based on mask-guided condititonal GANs, which can synthesize diverse, high-quality and controllable facial images from given masks. With the changeable input facial mask and source image, this method allows users to do high-level portrait editing.

Citation

If you find our code helpful for your research, please consider citing:

@inproceedings{gu2019mask,
  title={Mask-Guided Portrait Editing With Conditional GANs},
  author={Gu, Shuyang and Bao, Jianmin and Yang, Hao and Chen, Dong and Wen, Fang and Yuan, Lu},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={3436--3445},
  year={2019}
} 

Getting Started

Prerequisite

Running code