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A Web-Based Artwork Editing System Empowered by Neural Style Transfer

  • Kenta Goto
  • Hiroaki NishinoEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 926)

Abstract

A technique called neural style transfer is an effective method for generating artistic images based on a deep learning technique. It can extract a mood of a specific painting and blends it with a different image. The original method, however, needs a high-performance computer to get an output image within a practical response time since the neural style transfer involves heavily-loaded processing. To solve the problem, we develop a web-based image editing system enabling users to readily access the function only by using a mobile device with a standard web browser and a network connection. The proposed system allows the users to easily generating a wide variety of artistic images like logos and image clips using the neural style transfer anywhere they have a connection to the Internet. We implement the system as a web application and conduct some experiments to verify the effectiveness of the system. We elaborate the implementation method, experimental results, and observations in this paper.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Graduate School of EngineeringOita UniversityOitaJapan
  2. 2.Faculty of Science and TechnologyOita UniversityOitaJapan

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