• Title/Summary/Keyword: BeautyGAN

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Makeup transfer by applying a loss function based on facial segmentation combining edge with color information (에지와 컬러 정보를 결합한 안면 분할 기반의 손실 함수를 적용한 메이크업 변환)

  • Lim, So-hyun;Chun, Jun-chul
    • Journal of Internet Computing and Services
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    • v.23 no.4
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    • pp.35-43
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    • 2022
  • Makeup is the most common way to improve a person's appearance. However, since makeup styles are very diverse, there are many time and cost problems for an individual to apply makeup directly to himself/herself.. Accordingly, the need for makeup automation is increasing. Makeup transfer is being studied for makeup automation. Makeup transfer is a field of applying makeup style to a face image without makeup. Makeup transfer can be divided into a traditional image processing-based method and a deep learning-based method. In particular, in deep learning-based methods, many studies based on Generative Adversarial Networks have been performed. However, both methods have disadvantages in that the resulting image is unnatural, the result of makeup conversion is not clear, and it is smeared or heavily influenced by the makeup style face image. In order to express the clear boundary of makeup and to alleviate the influence of makeup style facial images, this study divides the makeup area and calculates the loss function using HoG (Histogram of Gradient). HoG is a method of extracting image features through the size and directionality of edges present in the image. Through this, we propose a makeup transfer network that performs robust learning on edges.By comparing the image generated through the proposed model with the image generated through BeautyGAN used as the base model, it was confirmed that the performance of the model proposed in this study was superior, and the method of using facial information that can be additionally presented as a future study.

A Comparative Study on the Color Decoration of Korean and Japanese Wooden Architecture (한(韓).일(日) 목조(木造)건축의 색채장식(色彩裝飾)에 대한 비교 - 근세 불사(佛寺)건축의 단청의장(丹靑意匠)을 중심으로 -)

  • Kim, Jung-Shin
    • Journal of architectural history
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    • v.7 no.4 s.17
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    • pp.151-163
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    • 1998
  • This Study is concerned with the color design of Korean and Japanese wooden architecture. The main subject of the study is to investigate the commonness and difference of color decoration between Korean and Japanese Buddhist 'Danchung' in the modern ages. In carrying this study into execution, I examined the architectural and historical backgrounds, and analysed the elements, techniques and principles of color design. The result of this study is as follows ; 1. 'Danchung' was originated from the practical functions in Chinese wooden architecture, and developed to embody sensuous beauty in Buddhist temple. The techniques and principles of color design and color tone of Korean and japanese Danchung had been similar in the ancient ages. But little by little they have differed in its function and color tone. So they are very different in modern times. 2. The dominant colors of Korean Danchung are red and green as 'Sang-nok Ha-dan(上綠下丹)', but Japanese's is only red as 'Bak-gan Juk-sun(白間赤線)' 3. Korean Danchung expresses and accentuates the important structural elements in three dimensions, on the other hand japanese Danchung takes two dimensional decoration on the unstructural elements 4. When seen in general, in Korean Danchung colors and their light and shade are simple and patternized. In the meantime, Japanese Danchung has many configurational expressions in general and is closed to paintings or picture.

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Development of a Web Service for Cosmetics Recommendation based on an Artificial Intelligence for User Personal Color Generation (사용자 퍼스널 컬러 생성을 위한 인공지능 기반 화장품 추천 웹 서비스 개발)

  • Suk-Hyung Hwang;Min-Taek Lim;Hun-Tae Hwang;Seung-Jun Lee;Soo-Hwan Kim;Se-Woong Hwang
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.461-463
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    • 2023
  • MZ세대를 중심으로 자기관리를 열심히 하는 사람들이 증가함에 따라 화장의 기본이 되는 개인 피부톤(퍼스널 컬러)을 찾는 것이 중요시되고 있다. 현재 대다수 사람은 자신에게 어울리는 퍼스널 컬러를 찾기 위해 높은 비용을 지불하여 전문가를 이용하거나 객관적이고 정량화된 기준 없이 오랜 시간을 투자하여 스스로 퍼스널 컬러를 찾는 등 시간과 비용 측면에서의 한계점을 가지고 있다. 본 논문에서는 이를 보완하기 위해 이미지 기반 인공지능 기술(객체 탐지, 객체 분할, BeautyGAN)을 적용하여 데이터 기반의 정량적인 기준을 생성하고, 퍼스널 컬러에 알맞은 화장품 추천 웹 서비스를 제안한다.

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