Skip to content
/ gans Public
forked from diegoalejogm/gans

Generative Adversarial Networks implemented in PyTorch and Tensorflow

License

Notifications You must be signed in to change notification settings

economy/gans

 
 

Repository files navigation

gans: Generative Adversarial Networks

Multiple Generative Adversarial Networks (GANs) implemented in PyTorch and Tensorflow.

Check out this blog post for an introduction to Generative Networks.

Vanilla GANs

Vanilla GANs found in this project were developed based on the original paper Generative Adversarial Networks by Goodfellow et al.

These are trained on the MNIST dataset, and learn to create hand-written digit images using a 1-Dimensional vector representation for 2D input images.

MNIST-like generated images before & after training.

DCGANs

Deep Convolutional Generative Adversarial Networks (DCGANs) in this repository were developed based on the original paper Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks by Radford et al.

These are trained on the CIFAR10 and the MNIST datasets. They use 3 dimensional representations for images (length x height x colors) directly for training.

CIFAR-like generated images before & after training.

About

Generative Adversarial Networks implemented in PyTorch and Tensorflow

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 99.5%
  • Python 0.5%