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IDEALLab / IH GAN CMAME 2022IH-GAN, data generation, and topology optimization code associated with our accepted CMAME 2022 paper: "IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures."
Xiaodong-Bran / MLFcGANXiaodong-Bran/MLFcGAN-Multilevel-Feature-Fusion-Based-Conditional-GAN-for-Underwater-Image-Color-Correction
GrepRunRepeat / Text To Image SynthesisText to image synthesis with GAN-CLS and MSGAN
bowenc0221 / MXNet GANMXNet Implementation of DCGAN, Conditional GAN, pix2pix
felipelodur / ManGANAssisting Colorization of Manga Characters Concept Art using Conditional GAN
s-chh / PyTorch GANsFrom scratch, simple and easy-to-understand Pytorch implementation of various generative adversarial network (GAN): GAN, DCGAN, Conditional GAN (cGAN), WGAN, WGAN-GP, CycleGAN, LSGAN, and StarGAN.
AdeelMufti / SNcGANSpectral Norm + Conditional GAN
EdWangLoDaSc / Prob CGAN For Drug DiscoveryA novel probabiliatic conditional GAN method to solve the Drug Activity question
rajatkb / Handloom Design Generation Using Deep Neural NetworksThis is our 7th sem 4th year Engineering final year project. It aims to use techniques like Conditional GAN , Image to Image translation , Texture and content transfer for aiding as a design tool for handloom weavers and also designers and industry as a whole.
arturml / Mnist CganA pytorch implementation of conditional GAN
SuihongSong / GeoModeling GANSim 2D Condition To Well Facies And Global FeaturesDirectly Conditional Facies Modeling Using an Improved Progressive Growing of Generative Adversarial Networks (GANs)
samfallahian / ContextAwareTabular CGANThis GitHub page is created for CA-CTGAN: Context Aware Conditional Tabular GAN for High-Fidelity Tabular Data Synthesis Using Transfer Learning
JensonZhu14 / AcGANThe implement attention conditional GANs (AcGAN) model.
marzekan / WCGAN GPTensorFlow 2 implementation of Wasserstein Conditional GAN with Gradient Penalty (WCGAN-GP) for synthetic data generation
vsooda / Mxnet Wganmxnet implement for Conditional Wasserstein GAN
harshitbansal05 / Image ColorizationImage Colorization of low resolution gray-scale images using Conditional Deep Convolutional Generative Adversarial Network(DC-GAN) in PyTorch.
hujinsen / Pytorch GAN CGANpytorch implementation of GAN and Conditional GAN
sangwoomo / GOLDMining GOLD Samples for Conditional GANs (NeurIPS 2019)
evanhu1 / Pytorch CelebA FaCeGANDeep convolutional conditional GAN implementation with CelebA dataset that allows for generation of custom faces according to textual input.
Mulham91 / Multi Spectral Image Synthesis For Crop Weed Segmentation In Precision FarmingIn this work, we propose an alternative solution with respect to the common data augmentation techniques, applying it to the fundamental problem of crop/weed segmentation in precision farming. Starting from real images, we create semi-artificial samples by replacing the most relevant object classes (i.e., crop and weeds) with synthesized counterparts. To do that, we employ a conditional GAN (cGAN), where the generative model is trained by conditioning the shape of the generated object. Moreover, in addition to RGB data, we take into account also near-infrared information, generating four channel multi-spectral synthetic images.
