Tensorflow implementation of VAE and GAN for MNIST
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Updated
Feb 23, 2018 - Python
Tensorflow implementation of VAE and GAN for MNIST
deep learning
This repo contains the implementation of a VAE and CVAE and applies that on MNIST dataset for modeling and generating different digits.
This is a "fork" of the Genhack3 repo for the Demeter's vision team solution.
VAE implementation for Deep Generative Models course
Handwritten Digit Generation with VAE and GAN are applied.
Unsupervised image-to-image translation framework using VAEs and GANs, designed to learn joint distributions across different domains. The project demonstrates high-quality image transformations and state-of-the-art domain adaptation performance on benchmark datasets.
Comparison of DCGAN, CapsuleGAN and Variational Autoencoder for Image Generation
Investigate mapping of articulations from the image space to the latent space using neural networks.
This repository is a comprehensive resource for mastering generative AI, featuring in-depth notes and exciting projects. The goal is to stay updated with the latest advancements in generative AI, and explore applications in image & video generation, creative content creation. Explore the limitless possibilities of generative AI today!
The semi-supervised GAN, or SGAN, model is an extension of the GAN architecture that involves the simultaneous training of a supervised discriminator, unsupervised discriminator, and a generator model. The result is both a supervised classification model that generalizes well to unseen examples and a generator model that outputs plausible exampl…
The Pytorch implementation of the NIPS 2018 paper
This project implements the BiCycleGAN architecture for multimodal image-to-image translation from scratch using PyTorch
This is a simplified implementation of VQ-GANs written in PyTorch. The architecture is borrowed from the paper "Taming Transformers for High-Resolution Image Synthesis".
work in-progress
A implement of GAN-collection for tensorflow version
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