35 Open Source Celeba Software Projects

[CVPR2020] Adversarial Latent Autoencoders

Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"

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

Implementations of (theoretical) generative adversarial networks and comparison without cherry-picking

Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"

Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets

Experiments for understanding disentanglement in VAE latent representations

Pytorch implementation of β-VAE

Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset

Simple Implementation of many GAN models with PyTorch.

PyTorch Implementation of InfoGAN

Pytorch implementation of FactorVAE proposed in Disentangling by Factorising(http://arxiv.org/abs/1802.05983)

MSG-GAN: Multi-Scale Gradients GAN (Architecture inspired from ProGAN but doesn't use layer-wise growing)

To obtain high resolution face images from CelebA

Tensorflow implementation of different GANs and their comparisions

Modified h5tool.py make user getting celeba-HQ easier

use yolo v2 to train face detection model on CelebA dataset

Who is your doppelgänger and more with Keras face recognition

Non-official + minimal reimplementation of HoloGAN by Nguyen-Phuoc, et al: https://arxiv.org/abs/1904.01326

PyTorch implementation of DCGAN

Download CelebA-HQ dataset easily ! Create with docker or download from Google Drive.

Torch implementation of "PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION"

PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)

Learning to Avoid Errors in GANs by Input Space Manipulation (Code for paper)

A Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"

Study Friendly Implementation of DCGAN in Tensorflow

Implementation of BEGAN in Pytorch and other interpolation experiments

A VAE for CelebA

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

Apply Thatcher illusion on a set of face photos

PyTorch implemented generative models for CelebA dataset: DCGAN, LSGAN, WGAN, WGANGP, InfoGAN, BEGAN, VAE, VAEGAN

Torch7 implementation of Unsupervised object learning from dense equivariant image labelling

Implementation of VAE and Style-GAN Architecture Achieving State of the Art Reconstruction

InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs, ICML 2020