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Torch Implemention of ECCV'16 paper: Attribute2Image

Attribute2Image

This is the code for ECCV 2016 paper Attribute2Image: Conditional Image Generation from Visual Attributes by Xinchen Yan, Jimei Yang, Kihyuk Sohn and Honglak Lee.

Please follow the instructions to run the code.

Requirements

Attribute2Image requires or works with

  • Mac OS X or Linux
  • NVIDIA GPU

Installing Dependency

Data Preprocessing

  • For LFW dataset, please run the script to download the pre-processed dataset
./prep_cropped_lfw.sh
  • Disclaimer: Please cite the LFW paper if you download this pre-processed version.

  • For CelebA dataset, please download the original dataset and then run the script for pre-processing

./prep_cropped_celeba.sh
  • Alternatively, you can download the pre-processed .t7 files with the following script:
./download_preprocessed_celeba.sh
  • Disclaimer: Please cite the CelebA paper if you download the pre-processed .t7 files.

  • For CUB dataset, please run the script to download the pre-processed dataset

./prep_cropped_cub.sh

Training (vanilla CVAE)

  • If you want to train the LFW image generator, please run the script (less than 3 hours on a single Titan X GPU)
./demo_lfw_trainCVAE.sh
  • If you want to train the CelebA image generator, please run the script (around 24 hours on a single Titan X GPU)
./demo_celeba_trainCVAE.sh

Training (disentangling CVAE)

  • If you want to train the LFW layered image generator, please run the script (less than 5 hours on a single Titan X GPU)
./demo_lfw_trainDisCVAE.sh
  • If you want to train the CUB layered image generator, please run the script (less than 3 hours on a single Titan X GPU)
./demo_cub_trainDisCVAE.sh

Visualization using Pre-trained Models

TBD

Citation

If you find this useful, please cite our work as follows:

@article{yan2015attribute2image,
  title={Attribute2Image: Conditional Image Generation from Visual Attributes},
  author={Yan, Xinchen and Yang, Jimei and Sohn, Kihyuk and Lee, Honglak},
  journal={arXiv preprint arXiv:1512.00570},
  year={2015}
}

Please contact "[email protected]" if any questions.