Category: GANs

Generative Adversarial Networks (GANs) have been used for many image processing tasks, among them, generating images from scratch (Style-based GANs) and applying new styles to images. A new paper, named InstaGAN, presents an innovative use of GANs – transfiguring instances of a given object in an image into another object while preserving the rest of […]

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 […]