Exploring Bridges Between Algorithmic and AI-generated Art
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866929687401332736 |
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| author | Wu, Jiaqi Adar, Eytan |
| author_facet | Wu, Jiaqi Adar, Eytan |
| contents | In this paper, we bridge algorithmic and AI art by adding functionality to the creative coding environment. We create two systems that demonstrate how AI features can enhance algorithmic art and, conversely, how AI art can be styled based on algorithmically-generated artifacts. The first library, GenP5, extends p5.js to allow the artist to apply diffusion models to style and 'condition' their algorithmically-constructed art. The second, P52Style, can learn the 'style' of an algorithmically generated artifact and apply that when creating new AI art. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_05508 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring Bridges Between Algorithmic and AI-generated Art Wu, Jiaqi Adar, Eytan Human-Computer Interaction In this paper, we bridge algorithmic and AI art by adding functionality to the creative coding environment. We create two systems that demonstrate how AI features can enhance algorithmic art and, conversely, how AI art can be styled based on algorithmically-generated artifacts. The first library, GenP5, extends p5.js to allow the artist to apply diffusion models to style and 'condition' their algorithmically-constructed art. The second, P52Style, can learn the 'style' of an algorithmically generated artifact and apply that when creating new AI art. |
| title | Exploring Bridges Between Algorithmic and AI-generated Art |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2406.05508 |