Von[NeurIPS 2018] Visual Object Networks: Image Generation with Disentangled 3D Representation.
Stars: ✭ 497 (+282.31%)
pytorch-gansPyTorch implementation of GANs (Generative Adversarial Networks). DCGAN, Pix2Pix, CycleGAN, SRGAN
Stars: ✭ 21 (-83.85%)
BicycleGANTensorflow implementation of the NIPS paper "Toward Multimodal Image-to-Image Translation"
Stars: ✭ 30 (-76.92%)
chainer-pix2pixChainer implementation for Image-to-Image Translation Using Conditional Adversarial Networks
Stars: ✭ 40 (-69.23%)
IganInteractive Image Generation via Generative Adversarial Networks
Stars: ✭ 3,845 (+2857.69%)
coursera-gan-specializationProgramming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Stars: ✭ 277 (+113.08%)
P2palaPage to PAGE Layout Analysis Tool
Stars: ✭ 147 (+13.08%)
tiny-pix2pixRedesigning the Pix2Pix model for small datasets with fewer parameters and different PatchGAN architecture
Stars: ✭ 21 (-83.85%)
BicycleganToward Multimodal Image-to-Image Translation
Stars: ✭ 1,215 (+834.62%)
Pix2pixhdSynthesizing and manipulating 2048x1024 images with conditional GANs
Stars: ✭ 5,553 (+4171.54%)
Pix2pixImage-to-image translation with conditional adversarial nets
Stars: ✭ 8,765 (+6642.31%)
CycleganSoftware that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Stars: ✭ 10,933 (+8310%)
Unet Stylegan2A Pytorch implementation of Stylegan2 with UNet Discriminator
Stars: ✭ 106 (-18.46%)
A Nice McCode for "A-NICE-MC: Adversarial Training for MCMC"
Stars: ✭ 115 (-11.54%)
Rectorchrectorch is a pytorch-based framework for state-of-the-art top-N recommendation
Stars: ✭ 121 (-6.92%)
Sketch To Art🖼 Create artwork from your casual sketch with GAN and style transfer
Stars: ✭ 115 (-11.54%)
ComicolorizationThis is the implementation of the "Comicolorization: Semi-automatic Manga Colorization"
Stars: ✭ 99 (-23.85%)
SketchyganCode for paper "SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis"
Stars: ✭ 113 (-13.08%)
Chemgan ChallengeCode for the paper: Benhenda, M. 2017. ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? arXiv preprint arXiv:1708.08227.
Stars: ✭ 98 (-24.62%)
Lggan[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation
Stars: ✭ 97 (-25.38%)
Mlds2018springMachine Learning and having it Deep and Structured (MLDS) in 2018 spring
Stars: ✭ 124 (-4.62%)
Capsule GanCode for my Master thesis on "Capsule Architecture as a Discriminator in Generative Adversarial Networks".
Stars: ✭ 120 (-7.69%)
GpndGenerative Probabilistic Novelty Detection with Adversarial Autoencoders
Stars: ✭ 112 (-13.85%)
Doppelganger[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
Stars: ✭ 97 (-25.38%)
3d Recgan🔥3D-RecGAN in Tensorflow (ICCV Workshops 2017)
Stars: ✭ 116 (-10.77%)
Pixel2style2pixelOfficial Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation"
Stars: ✭ 1,395 (+973.08%)
Tensorflow Mnist Cgan CdcganTensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.
Stars: ✭ 122 (-6.15%)
NatsrNatural and Realistic Single Image Super-Resolution with Explicit Natural Manifold Discrimination (CVPR, 2019)
Stars: ✭ 105 (-19.23%)
Hccg CycleganHandwritten Chinese Characters Generation
Stars: ✭ 115 (-11.54%)
DeliganThis project is an implementation of the Generative Adversarial Network proposed in our CVPR 2017 paper - DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data. DeLiGAN is a simple but effective modification of the GAN framework and aims to improve performance on datasets which are diverse yet small in size.
Stars: ✭ 103 (-20.77%)
Pytorch StudioganStudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
Stars: ✭ 2,325 (+1688.46%)
Pytorch cppDeep Learning sample programs using PyTorch in C++
Stars: ✭ 114 (-12.31%)
Lsd SegLearning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
Stars: ✭ 99 (-23.85%)
MganMasking GAN - Image attribute mask generation
Stars: ✭ 120 (-7.69%)
DeepnudecliDeepNude Command Line Version With Watermark Removed
Stars: ✭ 112 (-13.85%)
TaganAn official PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language", NeurIPS 2018
Stars: ✭ 97 (-25.38%)
Person removerPeople removal in images using Pix2Pix and YOLO.
Stars: ✭ 96 (-26.15%)
Textsum GanTensorflow re-implementation of GAN for text summarization
Stars: ✭ 111 (-14.62%)
PorousmediaganReconstruction of three-dimensional porous media using generative adversarial neural networks
Stars: ✭ 94 (-27.69%)
Wasserstein GanChainer implementation of Wasserstein GAN
Stars: ✭ 95 (-26.92%)
Stylegan WebA web porting for NVlabs' StyleGAN.
Stars: ✭ 112 (-13.85%)
Sprint ganPrivacy-preserving generative deep neural networks support clinical data sharing
Stars: ✭ 92 (-29.23%)
SpecganSpecGAN - generate audio with adversarial training
Stars: ✭ 92 (-29.23%)
DmtDisentangled Makeup Transfer with Generative Adversarial Network
Stars: ✭ 90 (-30.77%)
3dpose ganThe authors' implementation of Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations
Stars: ✭ 124 (-4.62%)
ChainercvChainerCV: a Library for Deep Learning in Computer Vision
Stars: ✭ 1,463 (+1025.38%)
CaloganGenerative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation
Stars: ✭ 87 (-33.08%)