Udacity DLND final project . Use GAN generate face
-
Updated
May 17, 2017 - HTML
Udacity DLND final project . Use GAN generate face
A Deep Convolutional Generative Adversarial Neural Networks to generate new images of faces
A DCGAN is trained on a dataset of faces. A generator network generates new images of faces that look very realistic.
This project is one of the projects required for Deep Learning Nanodegree
Udacity Deep Learning Nanodegree Face Generation PyTorch Project using DCGAN
Face generation bot utilizing DCGAN structure with TensorFlow.
Face Generation - Udacity project for deep learning Nanodegree
A game about smash or pass
GAN that can generate face images.
Face generation with DCGAN and SNGAN on CelebA dataset
Face generation with deep convolutional generative adversarial network using PyTorch and Jupyter Notebook.
Face generation using generative adversarial networks to generate new images
Implementation of Perceptual Generative Autoencoders in PyTorch
DCGAN that generates realistic human faces.
A demo project that manipulate face attributes using pretrained AttGAN model
In this project, we worked on generating realistic looking human faces using Generative Adversarial Networks.
Face generation with DCGAN
Add a description, image, and links to the face-generation topic page so that developers can more easily learn about it.
To associate your repository with the face-generation topic, visit your repo's landing page and select "manage topics."