/Variational-Autoencoder-PyTorch

Variational Autoencoder implemented with PyTorch, Trained over CelebA Dataset

Primary LanguagePython

Variational Autoencoder for face image generation in PyTorch

Variational Autoencoder for face image generation implemented with PyTorch, Trained over a combination of CelebA + FaceScrub + JAFFE datasets.

Based on Deep Feature Consistent Variational Autoencoder (https://arxiv.org/abs/1610.00291 | https://github.com/houxianxu/DFC-VAE)

TODO: Add DFC-VAE implementation

Pretrained model available at https://drive.google.com/open?id=0B4y-iigc5IzcTlJfYlJyaF9ndlU

Results

Original Faces vs. Reconstructed Faces:

Linear interpolation between two face images:

Vector arithmatic in latent space: