Non-Official Pytorch implementation of "Face Identity Disentanglement via Latent Space Mapping" https://arxiv.org/abs/2005.07728 Using StyleGAN2 instead of StyleGAN
Pytorch implementation of the paper Face Identity Disentanglement via Latent Space Mapping for both training and evaluation, with StyleGAN 2.
We used several pretrained models:
Weight files attached at this Drive folder.
You can also find at the above link our environment.yml file to create a relevant conda environment.
The dataset is comprised of StyleGAN 2 generated images and W latent codes. see Utils/data_creator.py.
Examples of our generated dataset attached at this Drive folder.
To train the model run train_script.py, you can change parameters in Configs/ folder.
Try Inference.ipynb notebook to disentangle identity from attributes by yourself
Our pretrained checkpoint attached at this Drive folder.