Skip to content

Tensorflow implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

Notifications You must be signed in to change notification settings

ChunyuanLI/DiscoGAN

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

30 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

DiscoGAN

Tensorflow implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks.

Recent development

Our NIPS paper ALICE improves DiscoGAN/CycleGAN/DualGAN, please see its code repo, and comparison on cartoon generation.

Alice4Alice: ALICE algorithms for painting the cartoon of Alice's Adventures in Wonderland

Prerequisites

  • Python 3.5
  • Tensorflow 1.0
  • Others

5-GMM to 2-GMM

The demo is tested a toy dataset, with domain X as 5-component GMM, and domain Z as 2-component GMM. It can be easily extended to other GMM settings, and real dataset.

To train:

$ python DiscoGAN_main.py

The reuslts:

Links

About

Tensorflow implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages