A simple conditional version of the Boundary Equilibrium Generative Adversarial Networks (CBEGANs)
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Updated
Jun 13, 2017 - Python
A simple conditional version of the Boundary Equilibrium Generative Adversarial Networks (CBEGANs)
Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.
Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset
Tensorflow implementation of pix2pix for various datasets.
PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)
Tensorflow implementation of simple Conditional Generative Adversarial Network(CGAN).
TensorFlow implementation of pix2pix
In terms of specific text description to generate corresponding images.
Conditional GAN
Conditional Generative Adversarial Networks (txt2img using conditional DCGAN).
A conditional DCGAN, in Tensorflow, for generating hand-written digits from the MNIST dataset.
Generation of MNIST like digits using Conditional Generative Adversarial Nets
Conditional anime generation using conditional GAN.
Investigation into Generative Neural Networks.
Deep learning works for ADLxMLDS (CSIE 5431) in NTU
cGANs for data augmentation, adversarial training, and transfer learning
Conditional Sequence Generative Adversarial Network trained with policy gradient, Implementation in Tensorflow
Text-to-Speech Synthesis by Generating Spectrograms using Generative Adversarial Network
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