DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 김주호 | - |
dc.contributor.author | Choi, DaEun | - |
dc.contributor.author | 최다은 | - |
dc.date.accessioned | 2024-08-08T19:30:14Z | - |
dc.date.available | 2024-08-08T19:30:14Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1097305&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/321780 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전산학부, 2024.2,[v, 51 p. :] | - |
dc.description.abstract | Graphic designers often get inspiration through the recombination of references. Our formative study (N=6) reveals that graphic designers focus on conceptual keywords during this process, and want support for discovering the keywords, expanding them, and exploring diverse recombination options of them, while still having room for their creativity. We propose CreativeConnect, a system with generative AI pipelines that helps users discover useful elements from the reference image using keywords, recommends relevant keywords, generates diverse recombination options with user-selected keywords, and shows recombinations as sketches with text descriptions. Our user study (N=16) showed that CreativeConnect helped users discover keywords from the reference and generate multiple ideas based on them, ultimately helping users produce more design ideas and higher self-reported creativity, compared to the baseline system without generative pipelines. While CreativeConnect was effective in ideation, we discussed how CreativeConnect can be extended to support other types of tasks in creativity support. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Creativity support tool▼aDesign ideation▼aReference recombination▼aGenerative AI | - |
dc.subject | 창의성 지원 도구▼a디자인 아이데이션▼a레퍼런스 재조합▼a생성형 인공지능 | - |
dc.title | CreativeConnect: supporting reference recombination for graphic design ideation with generative AI | - |
dc.title.alternative | 생성형 AI 기반 레퍼런스 재조합을 통한 그래픽 디자인 아이디에이션 과정 지원 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전산학부, | - |
dc.contributor.alternativeauthor | Kim, Juho | - |
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