The mel spectrogram generator using conditional WGAN-GP. For the mel spectrogram inverter, look up HiFi-GAN
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Updated
Aug 14, 2023 - Python
The mel spectrogram generator using conditional WGAN-GP. For the mel spectrogram inverter, look up HiFi-GAN
Image Generation using Generative Adversarial Networks (GANs) on MNIST dataset
PyTorch implementation of 'Pix2Pix' (Isola et al., 2017) and training it on Facades and Google Maps
Predicting strong gravitational lens wavelength information in JWST NIRcam imaging as observed by Euclid VIS/NISP
Source code and pretrained models for pix2pix - Inference on image and paint using pyqt5
TensorFlow implementation of Conditional Generative Adversarial Nets (CGAN) with MNIST dataset.
Conditional Generative Adversarial Network for generating synthetic faces with user specified attributes
SAGAN that conducted a CT noise reduction study based on conditional GAN
Ancient coins reconstruction using CGANs
Using pix2pix and SinGAN to get into the movie
A Tensorflow 2 implementation of SNGAN and Projection Discriminator
Enhancement and Segmentation GAN
Efficient Subsampling of Realistic Images From GANs Conditional on a Class or a Continuous Variable
Using a GAN to synthetically generate medical images for DL purposes
Conditional Generative Adversarial Networks(cgans) to convert text to image implemented in Python and TensorFlow & Keras
PANDA (Pytorch) pipeline, is a computational toolbox (MATLAB + pytorch) for generating PET navigators using Generative Adversarial networks.
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