AvatarGANGenerate Cartoon Images using Generative Adversarial Network
Stars: ✭ 24 (-87.69%)
keras-3dganKeras implementation of 3D Generative Adversarial Network.
Stars: ✭ 20 (-89.74%)
DeepFlowPytorch implementation of "DeepFlow: History Matching in the Space of Deep Generative Models"
Stars: ✭ 24 (-87.69%)
P2palaPage to PAGE Layout Analysis Tool
Stars: ✭ 147 (-24.62%)
Makegirlsmoe webCreate Anime Characters with MakeGirlsMoe
Stars: ✭ 3,144 (+1512.31%)
DcganThe Simplest DCGAN Implementation
Stars: ✭ 286 (+46.67%)
Faceswap GanA denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
Stars: ✭ 3,099 (+1489.23%)
Gan PlaygroundGAN Playground - Experiment with Generative Adversarial Nets in your browser. An introduction to GANs.
Stars: ✭ 336 (+72.31%)
Seq2seq Chatbot For KerasThis repository contains a new generative model of chatbot based on seq2seq modeling.
Stars: ✭ 322 (+65.13%)
steam-stylegan2Train a StyleGAN2 model on Colaboratory to generate Steam banners.
Stars: ✭ 30 (-84.62%)
SimganImplementation of Apple's Learning from Simulated and Unsupervised Images through Adversarial Training
Stars: ✭ 406 (+108.21%)
Simgan CaptchaSolve captcha without manually labeling a training set
Stars: ✭ 405 (+107.69%)
Wassersteingan.tensorflowTensorflow implementation of Wasserstein GAN - arxiv: https://arxiv.org/abs/1701.07875
Stars: ✭ 419 (+114.87%)
Pytorch RlThis repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
Stars: ✭ 394 (+102.05%)
Generative CompressionTensorFlow Implementation of Generative Adversarial Networks for Extreme Learned Image Compression
Stars: ✭ 428 (+119.49%)
Gan2shapeCode for GAN2Shape (ICLR2021 oral)
Stars: ✭ 183 (-6.15%)
IganInteractive Image Generation via Generative Adversarial Networks
Stars: ✭ 3,845 (+1871.79%)
SeqganA simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)
Stars: ✭ 502 (+157.44%)
Ssgan TensorflowA Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).
Stars: ✭ 496 (+154.36%)
UnetganOfficial Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)
Stars: ✭ 139 (-28.72%)
T2fT2F: text to face generation using Deep Learning
Stars: ✭ 494 (+153.33%)
Pix2pixhdSynthesizing and manipulating 2048x1024 images with conditional GANs
Stars: ✭ 5,553 (+2747.69%)
Awesome GansAwesome Generative Adversarial Networks with tensorflow
Stars: ✭ 585 (+200%)
All About The GanAll About the GANs(Generative Adversarial Networks) - Summarized lists for GAN
Stars: ✭ 630 (+223.08%)
GAN-auto-writeGenerative Adversarial Network that learns to generate handwritten digits. (Learning Purposes)
Stars: ✭ 18 (-90.77%)
Gans In ActionCompanion repository to GANs in Action: Deep learning with Generative Adversarial Networks
Stars: ✭ 748 (+283.59%)
Context Encoder[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs
Stars: ✭ 731 (+274.87%)
Deep Learning With PythonExample projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
Stars: ✭ 134 (-31.28%)
Fewshot Face Translation GanGenerative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.
Stars: ✭ 705 (+261.54%)
St CganDataset and Code for our CVPR'18 paper ST-CGAN: "Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal"
Stars: ✭ 13 (-93.33%)
MuseganAn AI for Music Generation
Stars: ✭ 794 (+307.18%)
Adversarial video generationA TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.
Stars: ✭ 662 (+239.49%)
Acgan PytorchPytorch implementation of Conditional Image Synthesis with Auxiliary Classifier GANs
Stars: ✭ 57 (-70.77%)
GanimationGANimation: Anatomically-aware Facial Animation from a Single Image (ECCV'18 Oral) [PyTorch]
Stars: ✭ 1,730 (+787.18%)
GandlfGenerative Adversarial Networks in Keras
Stars: ✭ 46 (-76.41%)
Dcgan TensorflowA Tensorflow implementation of Deep Convolutional Generative Adversarial Networks trained on Fashion-MNIST, CIFAR-10, etc.
Stars: ✭ 70 (-64.1%)
Pacgan[NeurIPS 2018] [JSAIT] PacGAN: The power of two samples in generative adversarial networks
Stars: ✭ 67 (-65.64%)
GanspaceDiscovering Interpretable GAN Controls [NeurIPS 2020]
Stars: ✭ 1,224 (+527.69%)
Pggan Pytorch🔥🔥 PyTorch implementation of "Progressive growing of GANs (PGGAN)" 🔥🔥
Stars: ✭ 653 (+234.87%)
CycleganSoftware that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Stars: ✭ 10,933 (+5506.67%)
Sprint ganPrivacy-preserving generative deep neural networks support clinical data sharing
Stars: ✭ 92 (-52.82%)
TaganAn official PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language", NeurIPS 2018
Stars: ✭ 97 (-50.26%)
SpecganSpecGAN - generate audio with adversarial training
Stars: ✭ 92 (-52.82%)
Lsd SegLearning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
Stars: ✭ 99 (-49.23%)
ExermoteUsing Machine Learning to predict the type of exercise from movement data
Stars: ✭ 108 (-44.62%)
StyleGANCppUnofficial implementation of StyleGAN's generator
Stars: ✭ 25 (-87.18%)
AdvSegLossOfficial Pytorch implementation of Adversarial Segmentation Loss for Sketch Colorization [ICIP 2021]
Stars: ✭ 24 (-87.69%)
Ad examplesA collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
Stars: ✭ 641 (+228.72%)
CaloganGenerative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation
Stars: ✭ 87 (-55.38%)
GpndGenerative Probabilistic Novelty Detection with Adversarial Autoencoders
Stars: ✭ 112 (-42.56%)
ShapeganGenerative Adversarial Networks and Autoencoders for 3D Shapes
Stars: ✭ 151 (-22.56%)