PyTorch implementations of Generative Adversarial Networks.
翻译 - 生成对抗网络的PyTorch实施。
#计算机科学#Image-to-Image Translation in PyTorch
翻译 - PyTorch中的图像到图像翻译
The author's officially unofficial PyTorch BigGAN implementation.
翻译 - 作者的官方非官方PyTorch BigGAN实现。
#计算机科学#StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
翻译 - StudioGAN是一个Pytorch库，为有条件/无条件图像生成提供了代表性的生成对抗网络（GAN）的实现。
A mix of GAN implementations including progressive growing
翻译 - GAN实施的混合，包括逐步增长
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
翻译 - 生成模型的集合，例如GAN，Pytorch和Tensorflow中的VAE。
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
A clean and readable Pytorch implementation of CycleGAN
Implementation A Style-Based Generator Architecture for Generative Adversarial Networks in PyTorch
TextGAN is a PyTorch framework for Generative Adversarial Networks (GANs) based text generation models.
(PyTorch) Implementations of GAN, Improved GAN, DCGAN, LAPGAN, and InfoGAN in PyTorch
Obj-GAN - Official PyTorch Implementation
Pytorch for Triple-GAN
See Triple-GAN-V2 in PyTorch: https://github.com/taufikxu/Triple-GAN
(Pytorch Implementation) GAN for image colorization
GANのpytorch実装
A very simple generative adversarial network (GAN) in PyTorch
翻译 - PyTorch中的一个非常简单的生成对抗网络（GAN）
gan, wgan-gp, anomaly detection, unsupervised, pytorch
Official PyTorch Implementation of GAN-Supervised Dense Visual Alignment
翻译 - GAN 监督的密集视觉对齐的官方 PyTorch 实现
gan, wgan-gp, anomaly detection, unsupervised, pytorch
PyTorch code for Triplet-GAN Paper
PyTorch implements of Auxiliary Classifier GAN
PyTorch Implementation of In-Domain GAN Inversion for StyleGAN2
[MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning. Pytorch Implementation
翻译 - [MSG-GAN]任何人都可以GAN！高度稳定和强大的体系结构。几乎不需要或不需要超参数调整。
For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.
Unofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN & HiFi-GAN & StyleMelGAN) with Pytorch
Official PyTorch implementation for paper: Diffusion-GAN: Training GANs with Diffusion
PyTorch implementation of C-RNN-GAN for Music Generation