name: wgandiv-pytorch
description: In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the fam- ily of Wasserstein GANs (WGANs) is considered to be state-of-the-art due to the theoretical contributions and competitive qualitative performance
license_spdx: Apache-2.0
version: 0.1.2
spec_version: 1.0
home_url: https://github.com/Lornatang/WassersteinGAN_DIV-PyTorch
news_url: https://libraries.io/pypi/wgandiv-pytorch/versions.atom
date: 2020-02-22
about_resource: NONE
libraries_io_url: https://libraries.io/pypi/wgandiv-pytorch?number=0.1.2
vcs_tool: git
vcs_repository: https://github.com/Lornatang/WassersteinGAN_DIV-PyTorch
vcs_branch: master
