Udacity DLND final project . Use GAN generate face
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Updated
May 17, 2017 - HTML
Udacity DLND final project . Use GAN generate face
Generative Adversarial Network (GAN) that generates face images.
Using generative adversarial networks to generate new images of faces (datasets: MNIST, CelebA).
Implementation of DCGAN in Tensorflow and Torch7
The aim of this work is to generate new face images similar to training ones (the CelebA dataset) according to user specified attributes. To do that we ended up with an implementation of a Versatile Auxiliary Classifier + GAN.
A Deep Convolutional Generative Adversarial Neural Networks to generate new images of faces
Tensorflow's 2.0 implementation of StackGANv2
A DCGAN is trained on a dataset of faces. A generator network generates new images of faces that look very realistic.
Generate new images of faces using Deep Convolutional Generative Adversarial Networks (DCGANs)
This project is one of the projects required for Deep Learning Nanodegree
Uses generative adversarial networks to create images of faces
Identify Human Face from Bare Description
Face generation bot utilizing DCGAN structure with TensorFlow.
A project for spouse prediction. Use deep learning and computer vision techniques to generate the appearance of a spouse.
Face Generation - Udacity project for deep learning Nanodegree
A game about smash or pass
GAN that can generate face images.
Using Generative Adversarial Neural Networks to generate new faces
Using DCGAN architecture to generate faces from CelebA dataset containing faces of some celebrities, made in PyTorch. Do 🌟 the repo if you find it useful.
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