https://github.com/achennu/variational-autoencoder-pytorch

Variational Autoencoder implemented with PyTorch, Trained over CelebA Dataset

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Variational Autoencoder implemented with PyTorch, Trained over CelebA Dataset

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Fork of bhpfelix/Variational-Autoencoder-PyTorch

Created about 6 years ago · Last pushed almost 9 years ago

https://github.com/achennu/Variational-Autoencoder-PyTorch/blob/master/

# 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: