A Collection of Variational Autoencoders (VAE) in PyTorch.

[CVPR 2021] A large-scale face image dataset that allows text-to-image generation, text-guided image manipulation, sketch-to-image generation, GANs for face generation and editing, image caption, and VQA

Variational auto-encoder trained on celebA . All rights reserved.

Get started with CelebA-HQ dataset in under 5 mins !

GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data

Using Capsule Networks in GANS to generate very realistic fake images that could perhaps be used for deepfakes

Code repository for "Interpretable and Accurate Fine-grained Recognition via Region Grouping", CVPR 2020 (Oral)

Variational Autoencoder trained by Feature Perceputal Loss

Example of vanilla VAE for face image generation at resolution 128x128 using pytorch.

👦 Human head semantic segmentation

Who is your doppelgänger and more with Keras face recognition

Code and notebooks related to the paper: "Reconstructing Faces from fMRI Patterns using Deep Generative Neural Networks" by VanRullen & Reddy, 2019

Generative Adversarial Networks in PyTorch

Official adversarial mixup resynthesis repository

Apply Thatcher illusion on a set of face photos

Conditional VAE in Tensorflow 2 | Conditional Image Generation | CelebA dataset

This repository is related to a project of the Introduction to Numerical Imaging (i.e, Introduction à l'Imagerie Numérique in French), given by the MVA Masters program at ENS-Paris Saclay. It was entirely build from scratch and contains code in PyTorch Lightning to train and then use a neural network for image classification. We used it to creat…

Code for the paper "Transfer Learning for Facial Attribute Prediction and Clustering" (iSCI 2019)

Trained an End-to-End model for deblurring of celebrity faces (CelebA).