Style-based GANs – Generating and Tuning Realistic Artificial Faces9 min read

Generative Adversarial Networks (GAN) are a relatively new concept in Machine Learning, introduced for the first time in 2014. Their goal is to synthesize artificial samples, such as images, that are indistinguishable from authentic images. A common example of a GAN application is to generate artificial face images by learning from a dataset of celebrity … Continue reading Style-based GANs – Generating and Tuning Realistic Artificial Faces9 min read