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
- Install Torch
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.