Bmsg Gan[MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning. Pytorch Implementation
Stars: ✭ 518 (-78.45%)
Munit TensorflowSimple Tensorflow implementation of "Multimodal Unsupervised Image-to-Image Translation" (ECCV 2018)
Stars: ✭ 292 (-87.85%)
Anogan KerasUnsupervised anomaly detection with generative model, keras implementation
Stars: ✭ 157 (-93.47%)
ImagedeblurringA Keras implementation of image deblurring based on ICCV 2017 paper "Deep Generative Filter for motion deblurring"
Stars: ✭ 72 (-97%)
Makegirlsmoe webCreate Anime Characters with MakeGirlsMoe
Stars: ✭ 3,144 (+30.78%)
Faceswap GanA denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
Stars: ✭ 3,099 (+28.91%)
ManMultinomial Adversarial Networks for Multi-Domain Text Classification (NAACL 2018)
Stars: ✭ 72 (-97%)
Gan MnistGenerative Adversarial Network for MNIST with tensorflow
Stars: ✭ 193 (-91.97%)
HidtOfficial repository for the paper "High-Resolution Daytime Translation Without Domain Labels" (CVPR2020, Oral)
Stars: ✭ 513 (-78.66%)
NgxNgx - Neural network based visual generator and mixer
Stars: ✭ 277 (-88.48%)
Dcgan TensorflowA Tensorflow implementation of Deep Convolutional Generative Adversarial Networks trained on Fashion-MNIST, CIFAR-10, etc.
Stars: ✭ 70 (-97.09%)
Mlds2018springMachine Learning and having it Deep and Structured (MLDS) in 2018 spring
Stars: ✭ 124 (-94.84%)
Face GeneratorGenerate human faces with neural networks
Stars: ✭ 266 (-88.94%)
Sequentialdata GanTensorflow Implementation of GAN modeling for sequential data
Stars: ✭ 69 (-97.13%)
SinganOfficial pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
Stars: ✭ 2,983 (+24.08%)
Zi2ziLearning Chinese Character style with conditional GAN
Stars: ✭ 1,988 (-17.3%)
Pacgan[NeurIPS 2018] [JSAIT] PacGAN: The power of two samples in generative adversarial networks
Stars: ✭ 67 (-97.21%)
Tensorflow Mnist Cgan CdcganTensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.
Stars: ✭ 122 (-94.93%)
traiNNertraiNNer: Deep learning framework for image and video super-resolution, restoration and image-to-image translation, for training and testing.
Stars: ✭ 130 (-94.59%)
FaceganTF implementation of our ECCV 2018 paper: Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model
Stars: ✭ 176 (-92.68%)
Anime Face Gan KerasA DCGAN to generate anime faces using custom mined dataset
Stars: ✭ 161 (-93.3%)
ApdrawingganCode for APDrawingGAN: Generating Artistic Portrait Drawings from Face Photos with Hierarchical GANs (CVPR 2019 Oral)
Stars: ✭ 510 (-78.79%)
Doppelganger[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
Stars: ✭ 97 (-95.97%)
Generative Adversarial NetworksIntroduction to generative adversarial networks, with code to accompany the O'Reilly tutorial on GANs
Stars: ✭ 505 (-78.99%)
lecam-ganRegularizing Generative Adversarial Networks under Limited Data (CVPR 2021)
Stars: ✭ 127 (-94.72%)
Esrgan Tf2ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks, published in ECCV 2018) implemented in Tensorflow 2.0+. This is an unofficial implementation. With Colab.
Stars: ✭ 61 (-97.46%)
HistoGANReference code for the paper HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms (CVPR 2021).
Stars: ✭ 158 (-93.43%)
Capsule GanCode for my Master thesis on "Capsule Architecture as a Discriminator in Generative Adversarial Networks".
Stars: ✭ 120 (-95.01%)
EigenGAN-TensorflowEigenGAN: Layer-Wise Eigen-Learning for GANs (ICCV 2021)
Stars: ✭ 294 (-87.77%)
Ai ArtPyTorch (and PyTorch Lightning) implementation of Neural Style Transfer, Pix2Pix, CycleGAN, and Deep Dream!
Stars: ✭ 153 (-93.64%)
Voice-Denoising-ANA Conditional Generative Adverserial Network (cGAN) was adapted for the task of source de-noising of noisy voice auditory images. The base architecture is adapted from Pix2Pix.
Stars: ✭ 42 (-98.25%)
Cyclegan QpOfficial PyTorch implementation of "Artist Style Transfer Via Quadratic Potential"
Stars: ✭ 59 (-97.55%)
ezganAn extremely simple generative adversarial network, built with TensorFlow
Stars: ✭ 36 (-98.5%)
DeepFlowPytorch implementation of "DeepFlow: History Matching in the Space of Deep Generative Models"
Stars: ✭ 24 (-99%)
Keras GanKeras implementations of Generative Adversarial Networks.
Stars: ✭ 8,494 (+253.33%)
StoryganStoryGAN: A Sequential Conditional GAN for Story Visualization
Stars: ✭ 184 (-92.35%)
SLE-GANTowards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis
Stars: ✭ 53 (-97.8%)
Acgan PytorchPytorch implementation of Conditional Image Synthesis with Auxiliary Classifier GANs
Stars: ✭ 57 (-97.63%)
http4s-munitIntegration between http4s & MUnit
Stars: ✭ 16 (-99.33%)
O GanO-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks
Stars: ✭ 117 (-95.13%)
MUST-GANPytorch implementation of CVPR2021 paper "MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generation"
Stars: ✭ 39 (-98.38%)
Facenet Face RecognitionThis is the research product of the thesis manifold Learning of Latent Space Vectors in GAN for Image Synthesis. This has an application to the research, name a facial recognition system. The application was developed by consulting the FaceNet model.
Stars: ✭ 54 (-97.75%)
ML-Papers-TLDRA summary of interesting Machine Learning (mostly Deep Learning) papers that I encounter.
Stars: ✭ 20 (-99.17%)
Pytorch GanA minimal implementaion (less than 150 lines of code with visualization) of DCGAN/WGAN in PyTorch with jupyter notebooks
Stars: ✭ 150 (-93.76%)
Gluon CvGluon CV Toolkit
Stars: ✭ 5,001 (+108.03%)
SeqganA simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)
Stars: ✭ 502 (-79.12%)
Text To ImageGenerative Adversarial Text to Image Synthesis / Please Star -->
Stars: ✭ 498 (-79.28%)
Person removerPeople removal in images using Pix2Pix and YOLO.
Stars: ✭ 96 (-96.01%)
Von[NeurIPS 2018] Visual Object Networks: Image Generation with Disentangled 3D Representation.
Stars: ✭ 497 (-79.33%)