인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
This study investigates the control of character deformation in comics and animation using image generation AI. While deformation is a complex concept shaped by culture, authorship, and style, its foundation lies in the distortion of human proportions. To establish an objective baseline, this research focuses on facial ratios and defines five deformation points from simplified to realistic. Representative images were collected from distinctive genres—wuxia, graphic novel, live action, shojo, and super-deformed—and used to construct standard reference images through prompt-based generation and quantitative validation. A LoRA model, named D-LoRA, was trained with proportion-based prompts to reproduce these deformation points. To evaluate its effectiveness, three datasets were compared: D-LoRA, prompt-only, and alternative style LoRA. Quantitative evaluation employed FaceMesh similarity, FID, KID, and CLIPScore. Results demonstrate that D-LoRA consistently outperformed other conditions, achieving higher facial ratio similarity, lower distribution divergence, and stronger text-image alignment. This study contributes by systematizing deformation analysis, establishing validated standard images, and integrating multiple quantitative metrics for objective evaluation. Limitations include the focus on facial ratios while excluding stylistic features such as hair or accessories. Future work will extend to diverse genres, ablation tests, full-body proportions, and emotional expression control.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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