Generative-ModelRepository for implementation of generative models with Tensorflow 1.x
Stars: ✭ 66 (+22.22%)
Mutual labels: dcgan, lsgan
gan-vae-pretrained-pytorchPretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
Stars: ✭ 134 (+148.15%)
Mutual labels: dcgan
prediction ganPyTorch Impl. of Prediction Optimizer (to stabilize GAN training)
Stars: ✭ 31 (-42.59%)
Mutual labels: dcgan
emotion-recognition-GANThis project is a semi-supervised approach to detect emotions on faces in-the-wild using GAN
Stars: ✭ 20 (-62.96%)
Mutual labels: dcgan
MXNet-GANMXNet Implementation of DCGAN, Conditional GAN, pix2pix
Stars: ✭ 23 (-57.41%)
Mutual labels: dcgan
cDCGANPyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)
Stars: ✭ 49 (-9.26%)
Mutual labels: dcgan
Fun-with-MNISTPlaying with MNIST. Machine Learning. Generative Models.
Stars: ✭ 23 (-57.41%)
Mutual labels: lsgan
WGAN-GP-TensorFlowTensorFlow implementations of Wasserstein GAN with Gradient Penalty (WGAN-GP), Least Squares GAN (LSGAN), GANs with the hinge loss.
Stars: ✭ 42 (-22.22%)
Mutual labels: lsgan
keras-text-to-imageTranslate text to image in Keras using GAN and Word2Vec as well as recurrent neural networks
Stars: ✭ 60 (+11.11%)
Mutual labels: dcgan
coursera-gan-specializationProgramming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Stars: ✭ 277 (+412.96%)
Mutual labels: dcgan
dcgan vae pytorchdcgan combined with vae in pytorch!
Stars: ✭ 110 (+103.7%)
Mutual labels: dcgan
Pytorch-conditional-GANsImplementation of Conditional Generative Adversarial Networks in PyTorch
Stars: ✭ 91 (+68.52%)
Mutual labels: dcgan
MMD-GANImproving MMD-GAN training with repulsive loss function
Stars: ✭ 82 (+51.85%)
Mutual labels: dcgan
pytorch-gansPyTorch implementation of GANs (Generative Adversarial Networks). DCGAN, Pix2Pix, CycleGAN, SRGAN
Stars: ✭ 21 (-61.11%)
Mutual labels: dcgan
Pytorch-Basic-GANsSimple Pytorch implementations of most used Generative Adversarial Network (GAN) varieties.
Stars: ✭ 101 (+87.04%)
Mutual labels: dcgan
DCGAN-PytorchA Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"
Stars: ✭ 23 (-57.41%)
Mutual labels: dcgan
GAN-Anime-CharactersApplied several Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN and StyleGAN to generate Anime Faces and Handwritten Digits.
Stars: ✭ 43 (-20.37%)
Mutual labels: dcgan
chainer-LSGANLeast Squares Generative Adversarial Network implemented in Chainer
Stars: ✭ 16 (-70.37%)
Mutual labels: lsgan
Advanced Models여러가지 유명한 신경망 모델들을 제공합니다. (DCGAN, VAE, Resnet 등등)
Stars: ✭ 48 (-11.11%)
Mutual labels: dcgan