Tensorflow Generative Model CollectionsCollection of generative models in Tensorflow
Stars: ✭ 3,785 (+15670.83%)
Mutual labels: generative-model, vae, generative-adversarial-networks, wgan, wgan-gp
Generative-ModelRepository for implementation of generative models with Tensorflow 1.x
Stars: ✭ 66 (+175%)
Mutual labels: vae, wgan, wgan-gp, stylegan
coursera-gan-specializationProgramming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Stars: ✭ 277 (+1054.17%)
Mutual labels: generative-model, gans, wgan, stylegan
Fun-with-MNISTPlaying with MNIST. Machine Learning. Generative Models.
Stars: ✭ 23 (-4.17%)
Mutual labels: vae, wgan, wgan-gp
Mimicry[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.
Stars: ✭ 458 (+1808.33%)
Mutual labels: gans, generative-adversarial-networks, wgan-gp
Tf.gans ComparisonImplementations of (theoretical) generative adversarial networks and comparison without cherry-picking
Stars: ✭ 477 (+1887.5%)
Mutual labels: gans, wgan, wgan-gp
stylegan-v[CVPR 2022] StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2
Stars: ✭ 136 (+466.67%)
Mutual labels: gans, generative-adversarial-networks, stylegan
Deeplearningmugenknockでぃーぷらーにんぐを無限にやってディープラーニングでDeepLearningするための実装CheatSheet
Stars: ✭ 684 (+2750%)
Mutual labels: vae, wgan, wgan-gp
Generative adversarial networks 101Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
Stars: ✭ 138 (+475%)
Mutual labels: gans, generative-adversarial-networks, wgan
Delving Deep Into GansGenerative Adversarial Networks (GANs) resources sorted by citations
Stars: ✭ 834 (+3375%)
Mutual labels: generative-model, gans, generative-adversarial-networks
TorchganResearch Framework for easy and efficient training of GANs based on Pytorch
Stars: ✭ 1,156 (+4716.67%)
Mutual labels: generative-model, gans, generative-adversarial-networks
Pytorch-Basic-GANsSimple Pytorch implementations of most used Generative Adversarial Network (GAN) varieties.
Stars: ✭ 101 (+320.83%)
Mutual labels: wgan, wgan-gp
InpaintNetCode accompanying ISMIR'19 paper titled "Learning to Traverse Latent Spaces for Musical Score Inpaintning"
Stars: ✭ 48 (+100%)
Mutual labels: generative-model, vae
progressive growing of GANsPure tensorflow implementation of progressive growing of GANs
Stars: ✭ 31 (+29.17%)
Mutual labels: wgan, wgan-gp
GAN-Anime-CharactersApplied several Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN and StyleGAN to generate Anime Faces and Handwritten Digits.
Stars: ✭ 43 (+79.17%)
Mutual labels: wgan, stylegan
Tf VqvaeTensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).
Stars: ✭ 226 (+841.67%)
Mutual labels: generative-model, vae
GDPPGenerator loss to reduce mode-collapse and to improve the generated samples quality.
Stars: ✭ 32 (+33.33%)
Mutual labels: generative-model, generative-adversarial-networks
vqvae-2PyTorch implementation of VQ-VAE-2 from "Generating Diverse High-Fidelity Images with VQ-VAE-2"
Stars: ✭ 65 (+170.83%)
Mutual labels: generative-model, vae
WGAN-GP-tensorflowTensorflow Implementation of Paper "Improved Training of Wasserstein GANs"
Stars: ✭ 23 (-4.17%)
Mutual labels: wgan, wgan-gp
