Multi-objective evolutionary GAN
Marco Baioletti, Carlos A. Coello Coello, Gabriele Di Bari, Valentina Poggioni
Abstract
Generative Adversarial Network (GAN) is a generative model proposed to imitate real data distributions. The original GAN algorithm has been found to be able to achieve excellent results for the image generation task, but it suffers from problems such as instability and mode collapse. To tackle these problems, many variants of the original model have been proposed; one of them is the Evolutionary GAN (EGAN), where a population of generators is evolved.
Topics & Concepts
Generative grammarComputer scienceTask (project management)Evolutionary algorithmGenerative adversarial networkArtificial intelligencePopulationMode (computer interface)Theoretical computer scienceImage (mathematics)EngineeringHuman–computer interactionSociologySystems engineeringDemographyGenerative Adversarial Networks and Image SynthesisAdvanced Vision and ImagingAdvanced Image Processing Techniques