A study of interior style transformation with GAN model

Jun-Hyeck Choi; Jae-Seung Lee

doi:10.13161/kibim.2022.12.1.055

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2022 Vol.12, Issue 1 Preview Page Next Page

A study of interior style transformation with GAN model GAN을 활용한 인테리어 스타일 변환 모델에 관한 연구

30 March 2022. pp. 55-61

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Abstract

Recently, demand for designing own space is increasing as the rapid growth of home furnishing market. However, there is a limitation that it is not easy to compare the style between before construction view and after view. This study aims to translate real image into another style with GAN model learned with interior images. To implement this, first we established style criteria and collected modern, natural, and classic style images, and experimented with ResNet, UNet, Gradient penalty concept to CycleGAN algorithm. As a result of training, model recognize common indoor image elements, such as floor, wall, and furniture, and suitable color, material was converted according to interior style. On the other hand, the form of furniture, ornaments, and detailed pattern expressions are difficult to be recognized by CycleGAN model, and the accuracy lacked. Although UNet converted images more radically than ResNet, it was more stained. The GAN algorithm allowed us to represent results within 2 seconds. Through this, it is possible to quickly and easily visualize and compare the front and after the interior space style to be constructed. Furthermore, this GAN will be available to use in the design rendering include interior.

Keywords

CycleGAN

Image Translation

Interior Style

Image Rendering

키워드

CycleGAN

이미지 변환

인테리어 스타일

이미지 렌더링

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Information

Publisher :Journal of KIBIM
Publisher(Ko) :한국BIM학회
Journal Title :Journal of KIBIM
Journal Title(Ko) :한국BIM학회논문집
Volume : 12
No :1
Pages :55-61
Received Date : 2022-01-24
Revised Date : 2022-02-08
Accepted Date : 2022-03-08
DOI :https://doi.org/10.13161/kibim.2022.12.1.055

Journal of KIBIM ISSN:2288-1697(Print) 2288-1697(Online) 한국BIM학회논문집

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