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DiscoGAN

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

Install / Use

/learn @ChunyuanLI/DiscoGAN
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

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:
<img src="results/DiscoGAN/Overall.png" width="600px">

Links

  • Official PyTorch implementation (https://github.com/SKTBrain/DiscoGAN)
  • Taehoon Kim's PyTorch implementation (https://github.com/carpedm20/DiscoGAN-pytorch)
View on GitHub
GitHub Stars48
CategoryEducation
Updated2y ago
Forks20

Languages

Python

Security Score

60/100

Audited on Jan 4, 2024

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