CreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AI
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866910355773456384 |
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| author | Choi, DaEun Hong, Sumin Park, Jeongeon Chung, John Joon Young Kim, Juho |
| author_facet | Choi, DaEun Hong, Sumin Park, Jeongeon Chung, John Joon Young Kim, Juho |
| contents | 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 designers' 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 with higher self-reported creativity compared to the baseline system without generative pipelines. While CreativeConnect was shown effective in ideation, we discussed how CreativeConnect can be extended to support other types of tasks in creativity support. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_11949 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | CreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AI Choi, DaEun Hong, Sumin Park, Jeongeon Chung, John Joon Young Kim, Juho Human-Computer Interaction 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 designers' 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 with higher self-reported creativity compared to the baseline system without generative pipelines. While CreativeConnect was shown effective in ideation, we discussed how CreativeConnect can be extended to support other types of tasks in creativity support. |
| title | CreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AI |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2312.11949 |