[CVPR2020] Adversarial Latent Autoencoders
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Updated
Jan 23, 2021 - Python
[CVPR2020] Adversarial Latent Autoencoders
A large-scale face dataset for face parsing, recognition, generation and editing.
Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"
Experiments for understanding disentanglement in VAE latent representations
Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset
Pytorch implementation of β-VAE
PyTorch Implementation of InfoGAN
Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"
Pytorch implementation of FactorVAE proposed in Disentangling by Factorising(http://arxiv.org/abs/1802.05983)
Tensorflow implementation of different GANs and their comparisions
MSG-GAN: Multi-Scale Gradients GAN (Architecture inspired from ProGAN but doesn't use layer-wise growing)
Code repository for "Interpretable and Accurate Fine-grained Recognition via Region Grouping", CVPR 2020 (Oral)
Get started with CelebA-HQ dataset in under 5 mins !
use yolo v2 to train face detection model on CelebA dataset
PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)
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