Generative Learning

Deep Learning can be used to generate complete new real-like data such as images, text and more. But how is that possible?

Autoencoders · Generative Learning · Unsupervised Learning

The theory behind Latent Variable Models: formulating a Variational Autoencoder

Explaining the mathematics behind generative learning and latent variable models and how Variational Autoencoders (VAE) were formulated (code included)

Generative Learning · Computer Vision

Deepfakes: Face synthesis with GANs and Autoencoders

A closer look on Deepfakes: face sythesis with StyleGAN, face swap with XceptionNet and facial attributes and expression manipulation with StarGAN

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - semantic image synthesis and learning a generative model from a single image

The sixth article-series of GAN in computer vision - we explore semantic image synthesis and learning a generative model from a single image

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - self-supervised adversarial training and high-resolution image synthesis with style incorporation

The fifth article-series of GAN in computer vision - we discuss self-supervision in adversarial training for unconditional image generation as well as in-layer normalization and style incorporation in high-resolution image synthesis.

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - 2K image and video synthesis, and large-scale class-conditional image generation

The fourth article-series of GAN in computer vision - we explore 2K image generation with a multi-scale GAN approach, video synthesis with temporal consistency, and large-scale class-conditional image generation in ImageNet.

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - Improved training with Wasserstein distance, game theory control and progressively growing schemes

The third article-series of GAN in computer vision - we encounter some of the most advanced training concepts such as Wasserstein distance, adopt a game theory aspect in the training of GAN, and study the incremental/progressive generative training to reach a megapixel resolution.

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - Conditional image synthesis and 3D object generation

The second article of the GANs in computer vision series - looking deeper in generative adversarial networks, mode collapse, conditional image synthesis, and 3D object generation, paired and unpaired image to image generation.

Generative Adversarial Networks · Generative Learning · Computer Vision

GANs in computer vision - Introduction to generative learning

The first article of the GANs in computer vision series - an introduction to generative learning, adversarial learning, gan training algorithm, conditional image generation, mode collapse, mutual information

Generative Learning · Generative Adversarial Networks

Decrypt Generative Adversarial Networks (GAN)

What's the difference of generative and discriminative models and what is a GAN

Autoencoders · Unsupervised Learning · Generative Learning · Pytorch

How to Generate Images using Autoencoders

Learn what autoencoders are and build one to generate new images