Deep learning approaches to pattern extraction and recognition in paintings and drawings: an overview
Giovanna Castellano, Gennaro Vessio
Abstract
Abstract This paper provides an overview of some of the most relevant deep learning approaches to pattern extraction and recognition in visual arts, particularly painting and drawing. Recent advances in deep learning and computer vision, coupled with the growing availability of large digitized visual art collections, have opened new opportunities for computer science researchers to assist the art community with automatic tools to analyse and further understand visual arts. Among other benefits, a deeper understanding of visual arts has the potential to make them more accessible to a wider population, ultimately supporting the spread of culture.
Topics & Concepts
PaintingComputer scienceDeep learningThe artsArtificial intelligenceVisual artsComputational Science and EngineeringPopulationMachine learningArtSociologyDemographyAesthetic Perception and AnalysisGenerative Adversarial Networks and Image SynthesisVisual Attention and Saliency Detection