A Machine Learning Application Based on Giorgio Morandi Still-life Paintings to Assist Artists in the Choice of 3D Compositions

Abstract

Abstract The authors present a system built to generate arrangements of threedimensional models for aesthetic evaluation, with the aim being to support an artist in their creative process. The authors explore how this system can automatically generate aesthetically pleasing content for use in the media and design industry, based on standards originally developed in master artworks. They then demonstrate the effectiveness of their process in the context of paintings using a collection of images inspired by the work of the artist Giorgio Morandi (Bologna, 1890–1964). Finally, they compare the results of their system with the results of a well-known Generative Adversarial Network (GAN).