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Authors: Akira Nakajima and Hiroyuki Kobayashi

Affiliation: Robotics & Design Engineering Osaka Institute of Technology University, Japan

Keyword(s): CycleGAN, Shape Transformation, Image Processing.

Abstract: AI technology has developed remarkably in recent years, and AI-based image generation tools have spread rapidly. CycleGAN is one of the image generation AIs and specializes in image style transformation, and has the problem of being able to change colors and patterns but not shapes. The reason may be that the model considers the background as a part of the conversion target, which can be solved by removing the background. In this study, the number of backgrounds is limited to a certain number, and CycleGAN is used for shape transformation.The evaluation is done by comparing the result of this experiment with the image transformation when the input is an image with the background removed.Comparison of the proposed and conventional methods showed comparable results.

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Paper citation in several formats:
Nakajima, A. and Kobayashi, H. (2023). Shape Transformation with CycleGAN Using an Automobile as an Example. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-670-5; ISSN 2184-2809, SciTePress, pages 736-739. DOI: 10.5220/0012233100003543

@conference{icinco23,
author={Akira Nakajima. and Hiroyuki Kobayashi.},
title={Shape Transformation with CycleGAN Using an Automobile as an Example},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2023},
pages={736-739},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012233100003543},
isbn={978-989-758-670-5},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Shape Transformation with CycleGAN Using an Automobile as an Example
SN - 978-989-758-670-5
IS - 2184-2809
AU - Nakajima, A.
AU - Kobayashi, H.
PY - 2023
SP - 736
EP - 739
DO - 10.5220/0012233100003543
PB - SciTePress