[CVPR2020] Adversarial Latent Autoencoders

papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

A large-scale face dataset for face parsing, recognition, generation and editing.

A face recognition solution on mobile device.

TF implementation of our ECCV 2018 paper: Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

[ECCV 2018] ReenactGAN: Learning to Reenact Faces via Boundary Transfer

Notebook for O'Reilly's "Deep Convolutional Generative Adversarial Networks"

This is the accompanying code for the Medium article: https://medium.com/@karol_majek/high-resolution-face2face-with-pix2pix-1024x1024-37b90c1ca7e8

Caffe/C++ implementation of Boundary Equilibrium Generative Adversarial Networks paper for face generation

Various implementations and projects on CNN, RNN, LSTM, GAN, etc

Deep Convolutional Conditional GAN and Supervised CNN for generating children's faces given parents' faces

Simple deepfake pet-project

Udacity nanodegree projects: DLND, DRLND, DAND

Generate new faces using GAN made in PyTorch.

Uses generative adversarial networks to create images of faces

face generating DCGAN implemented by Keras

Controllable Face Generation via pretrained Conditional Adversarial Latent Autoencoder (ALAE)

Generate Random Faces which do not exists. I trained a Deep Convolution GAN (DCGAN) on 100k celebrities photos.

在该项目中，你将使用生成式对抗网络（Generative Adversarial Nets）来生成新的人脸图像。

Using GAN to generate human faces (Tensorflow).

Contains my experiments with GANs.

Generating faces using a variational autoencoder in Keras with Tensorflow

VoiceGAN - Hallucinating Faces from Voices

using GANs generate face.

Implementation of DCGAN in Tensorflow and Torch7

Using Generative Adversarial Neural Networks to generate new faces

This is the project submitted as a part of Facebook PyTorch challenge scholarship Deep Learning Nanodegree program. The original repo of Udacity can be found at https://github.com/udacity/deep-learning-v2-pytorch

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.

Use a DCGAN on the CelebA dataset to generate images of novel and realistic human faces.

DCGAN architecture to generate faces from CelebA dataset, made with ❤️ in PyTorch. Do 🌟 the repo if you find it useful.