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#

cdcgan

Here are 23 public repositories matching this topic...

Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset

  • UpdatedAug 22, 2017
  • Python

PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)

  • UpdatedAug 28, 2017
  • Python

A conditional DCGAN, in Tensorflow, for generating hand-written digits from the MNIST dataset.

  • UpdatedJul 18, 2018
  • Python

We use Conditional-DCGAN to generate animated faces 👫 and emojis 😃 using pytorch

  • UpdatedMay 29, 2018
  • Jupyter Notebook

Conditional Deep Convolutional GAN implementation using pytorch on MNIST dataset.

  • UpdatedSep 28, 2022
  • Jupyter Notebook

A small overview of what GANs and their main variants are, with related implementations.

  • UpdatedMar 28, 2023
  • Python

Study Generative Adversarial Networks

  • UpdatedAug 20, 2019
  • Python

神经网络模型训练研究学习

  • UpdatedJan 22, 2024
  • Python

Simple and intuitive implementations of Generative Adversarial Networks with pytorch

  • UpdatedJul 31, 2018
  • Jupyter Notebook

This Repository contain an IPython notebook of an example implementation of conditional Deep Convolutional Generative Adversarial Networks or cDCGAN or DC cGAN using Tensorflow.Keras Funtional API.

  • UpdatedMay 25, 2021
  • Jupyter Notebook

cDCGAN model for audio-to-image generation: a cross-modal analysis using deep-learning techniques

  • UpdatedJan 10, 2024
  • Python

Step by step Generative Adversarial Networks and Conditional GAN building using Pytorch

  • UpdatedNov 5, 2020
  • Jupyter Notebook

General Adversial Networks using Few shot learning

  • UpdatedMay 13, 2019
  • Python

GAN-based framework to generate depth images of infants from a desired image and pose

  • UpdatedMar 16, 2022
  • Python

conditionalDCGAN for MNIST with chainer

  • UpdatedJun 23, 2018
  • Python

A Conditional Deep Convolutional Generative Adversarial Network implemented in PyTorch, trained on the Fashion MNIST dataset.

  • UpdatedApr 9, 2024
  • Jupyter Notebook

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