This is the offcial implementation of paper 'MorphGANFormer: Transformer-based Face Morphing and De-Morphing'. Code will be coming soon.
This repository contains the implementation of:
- MorphGANFormer
- Morphing and De-morphing
Our model is based on the paper: GANformer: Generative Adversarial Transformers [Github] [Arxiv]
Inspired by GANformer, we introduce a transformer-based face morphing algorithm. Special loss functions are designed to support the optimization of face morphing process. We extend the study of transformer-based face morphing to demorphing by presenting an effective defense strategy with access to a reference image using the same generator of MorphGANFormer. Such demorphing is conceptually similar to unmixing of hyperspectral images but operates in the latent (instead of pixel) space.
- Python 3.6 or 3.7 are supported.
- Pytorch >= 1.8.
- CUDA 10.0 toolkit and cuDNN 7.5.
- See
requirements.txtfor the required python packages and runpip install -r requirements.txtto install them.
