한국정보처리학회:학술대회논문집 (Proceedings of the Korea Information Processing Society Conference)

한국정보처리학회 (Korea Information Processing Society)
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GAN 및 키포인트와 로컬 아핀 변환을 이용한 스타일 변환 동적인 이미지 애니메이션 네트워크 구축

Construction of Dynamic Image Animation Network for Style Transformation Using GAN, Keypoint and Local Affine

  • 장준보 (한국외국어대학교 산업경영공학과)
  • Jang, Jun-Bo (Dept. of Industrial Management Engineering, Hankuk University of Foreign Studies)
  • 발행 : 2022.05.17
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초록

High-quality images and videos are being generated as technologies for deep learning-based image style translation and conversion of static images into dynamic images have developed. However, it takes a lot of time and resources to manually transform images, as well as professional knowledge due to the difficulty of natural image transformation. Therefore, in this paper, we study natural style mixing through a style conversion network using GAN and natural dynamic image generation using the First Order Motion Model network (FOMM).

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