Generate Faces using GANs (Part of Udacity's DLFND)
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Updated
May 15, 2017 - HTML
Generate Faces using GANs (Part of Udacity's DLFND)
We aim to generate realistic images from text descriptions using GAN architecture. The network that we have designed is used for image generation for two datasets: MSCOCO and CUBS.
👨🦰 Large Scale Active Social Engineering Defense (ASED): Multimedia and Social Engineering
A PyTorch implementation of "Deep Convolutional Generative Adversarial Networks" with Multiple Discriminator.
Project 5
Generative Adverserial Network for face generation using Tensorflow and DCGAN architecture
Defined and trained a DCGAN on a dataset of faces. The Goal of this project is to generate new images of faces that look as realistic as possible.
Implementation of Conditional Deep Convolutional GANs in low-level APIs
DCGAN architecture to generate faces from CelebA dataset, made with ❤️ in PyTorch. Do 🌟 the repo if you find it useful.
A generative adversarial network that trains on photos celebrities faces to produce new realistic face images
Deep Convolutional Generative Adversarial Network for Street View House Numbers dataset.
Udacity Deep Learning Project 5 Face Generation Using DCGAN
A Generative Adversarial Network to generate faces
Generate new images of faces that look as realistic as possible with DCGANs
Define and Train DCGAN generator network to generate new images of faces that look as realistic as possible.
A generative adversarial network (GAN) that generates images of faces.
Generate New Faces Using Deep Convolutional Generative Adversarial Networks/ Project 5 of the DLNDF
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