There are 1 repository under lsgan topic.
Collection of generative models in Tensorflow
Collection of generative models in Pytorch version.
Awesome Generative Adversarial Networks with tensorflow
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Implementations of (theoretical) generative adversarial networks and comparison without cherry-picking
Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
DCGAN LSGAN WGAN-GP DRAGAN PyTorch
MATLAB implementations of Generative Adversarial Networks -- from GAN to Pixel2Pixel, CycleGAN
🚀 Variants of GANs most easily implemented as TensorFlow2. GAN, DCGAN, LSGAN, WGAN, WGAN-GP, DRAGAN, ETC...
Repository for implementation of generative models with Tensorflow 1.x
【X世纪星际终端】A Wechat Social and AR Game: 基于微信聊天,结合增强现实技术AR+LBS(基于图像位置)的轻社交星际漂流瓶游戏。向外太空发送漂流信息,看看AI预测的外星人是长什么样的,寻找身边的外星人,逗逗外星生物,看看外星植物及外星建筑。Send the message to the outer space, find the aliens in the earth. Let`s see what they look like from LSGAN`s prediction. Also, Have a look at the aliens' pets and the vegetation from the outer space
TensorFlow implementations of Wasserstein GAN with Gradient Penalty (WGAN-GP), Least Squares GAN (LSGAN), GANs with the hinge loss.
PyTorch implemented generative models for CelebA dataset: DCGAN, LSGAN, WGAN, WGANGP, InfoGAN, BEGAN, VAE, VAEGAN
Generative Adversarial Networks with TensorFlow2, Keras and Python (Jupyter Notebooks Implementations)
[CVPR 2021: Oral] In this work, we show that high frequency Fourier spectrum decay discrepancies are not inherent characteristics for existing CNN-based generative models.
Playing with MNIST. Machine Learning. Generative Models.
Least Squares Generative Adversarial Network implemented in Chainer
Beginner's Guide to building GAN from scratch with Tensorflow and Keras
implement GANs and VAE using pytorch
Repository for my research on generative modelling of cell images
Tutorial introduction slides to GANs. Code implementations and links of relevant papers.
Repo of my master thesis at Pompeu Fabra University: "Towards album artwork generation based on audio". We analyze VAEs and GANs to condition image generation with audio.
The GAN Book: Train stable Generative Adversarial Networks using TensorFlow2, Keras and Python.
GAN / DCGAN / InfoGAN / BEGAN ...
Generate Faces Using Deep Convolutional Generative Adversarial Networks (DCGAN)
Implements gans on toy datasets and preliminary ML datasets for showing certain aspects of convergence and stability. Tries to cover various loss functions defined over the years.
PyTorch implementation of the Least Squares Generative Adversarial Networks