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StackGAN-pytorch

Pytorch implementation for reproducing COCO results in the paper StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks by Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, Dimitris Metaxas. The network structure is slightly different from the tensorflow implementation.

<img src="examples/framework.jpg" width="850px" height="370px"/>

Dependencies

python 2.7

Pytorch

In addition, please add the project folder to PYTHONPATH and pip install the following packages:

Data

  1. Download our preprocessed char-CNN-RNN text embeddings for training coco and evaluating coco, save them to data/coco.
  1. Download the coco image data. Extract them to data/coco/.

Training

Pretrained Model

Evaluating

Examples for COCO:

Save your favorite pictures generated by our models since the randomness from noise z and conditioning augmentation makes them creative enough to generate objects with different poses and viewpoints from the same discription :smiley:

Citing StackGAN

If you find StackGAN useful in your research, please consider citing:

@inproceedings{han2017stackgan,
Author = {Han Zhang and Tao Xu and Hongsheng Li and Shaoting Zhang and Xiaogang Wang and Xiaolei Huang and Dimitris Metaxas},
Title = {StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks},
Year = {2017},
booktitle = {{ICCV}},
}

Our follow-up work

References