tensorflow-generative-model-collections

GitHub describes it as Collection of generative models in Tensorflow. The repository metadata lists Python as its primary language. The metadata lists the Apache-2.0 license. This article stays within the project description and details documented in the GitHub repository README.

GitHub describes it as Collection of generative models in Tensorflow. The repository metadata lists Python as its primary language. The metadata lists the Apache-2.0 license. The README describes the project this way: Pytorch version of this repository is availabel at https://github.com/znxlwm/pytorch-generative-model-collections

The README section ""Are GANs Created Equal? A Large-Scale Study" Paper" states: https://github.com/google/compare gan is the code that was used in the paper. It provides IS/FID and rich experimental results for all gan-variants.

The README section "Lists" states: Name | Paper Link | Value Function :---: | :---: | :--- | GAN | Arxiv | LSGAN | Arxiv | WGAN | Arxiv | WGAN GP | Arxiv | DRAGAN | Arxiv | CGAN | Arxiv | infoGAN | Arxiv | ACGAN | Arxiv | EBGAN | Arxiv | BEGAN | Arxiv |

The README section "Results for mnist" states: Network architecture of generator and discriminator is the exaclty sames as in infoGAN paper. For fair comparison of core ideas in all gan variants, all implementations for network architecture are kept same except EBGAN and BEGAN. Small modification is made for EBGAN/BEGAN, since those adopt auto-encoder strucutre for discriminator. But I tried to keep the capacity of discirminator.

The repository README is the source for this review. It does not replace a local installation or an independent test.

• Source 1 · Project repository
• Source 2 · README