SCGAN

An official PyTorch Implementation of paper "Spatially Constrained GAN for Face and Fashion Synthesis"

This repo is still under construction

By Songyao Jiang, Hongfu Liu, Yue Wu and Yun Fu.

Smile Lab @ Northeastern University

Data Preparation

1. Download CelebA Dataset. We used their aligned&cropped version. Preprocessed segmentation data for CelebA is provided at GoogleDrive.

2. Download DeepFashion Dataset. We used their Fashion Synthesis Subset

Train

bash scripts/train_celeba_command.sh
bash scripts/train_fashion_command.sh

Test

bash scripts/test_celeba_command.sh
bash scripts/test_fashion_command.sh

Citation

If you find this repo useful in your research, please consider citing

@inproceedings{jiang2021spatially,
  title={Spatially Constrained GAN for Face and Fashion Synthesis},
  author={Jiang, Songyao and Hongfu Liu and Yue Wu and Fu, Yun},
  booktitle={2021 16th IEEE International Conference on Automatic Face \& Gesture Recognition (FG 2021)},
  year={2021},
  organization={IEEE}
}

@inproceedings{jiang2019segmentation,
  title={Segmentation guided image-to-image translation with adversarial networks},
  author={Jiang, Songyao and Tao, Zhiqiang and Fu, Yun},
  booktitle={2019 14th IEEE International Conference on Automatic Face \& Gesture Recognition (FG 2019)},
  pages={1--7},
  year={2019},
  organization={IEEE}
}