Progressively growing of GANs Pytorch Implementation
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Updated
Nov 9, 2017 - Python
Progressively growing of GANs Pytorch Implementation
Pure tensorflow implementation of progressive growing of GANs
A straightforward implementation for Progressive Growing of GANs
A PyTorch 0.4 implementation of Progressive Growing of GANs for Improved Quality, Stability and Variability (https://arxiv.org/abs/1710.10196)
Pytorch implementation of progressive growing gan
A python abstraction for Progressively Trained Generative Adversarial Network (PGGAN) training based on PyTorch.
Implementation of NVIDIA's Progressive Growing of GANs
Convolutional autoencoder able to change image attributes
A collection of deep learning models (PyTorch implemtation)
Implementation of some different variants of GANs by tensorflow, Train the GAN in Google Cloud Colab, DCGAN, WGAN, WGAN-GP, LSGAN, SNGAN, RSGAN, RaSGAN, BEGAN, ACGAN, PGGAN, pix2pix, BigGAN
Pytorch implementations of GANs
PyTorch implementation of 'PGGAN' (Karras et al., 2018) from scratch and training it on CelebA-HQ at 512 × 512
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