| Autor: |
Junming Chen, Duolin Wang, Zichun Shao, Xu Zhang, Mengchao Ruan, Huiting Li, Jiaqi Li |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Buildings, Vol 13, Iss 9, p 2285 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2075-5309 |
| DOI: |
10.3390/buildings13092285 |
| Popis: |
The exceptional architecture designed by master architects is a shared treasure of humanity, which embodies their design skills and concepts not possessed by common architectural designers. To help ordinary designers improve the design quality, we propose a new artificial intelligence (AI) method for generative architectural design, which generates designs with specified styles and master architect quality through a diffusion model based on textual prompts of the design requirements. Compared to conventional methods dependent on heavy intellectual labor for innovative design and drawing, the proposed method substantially enhances the creativity and efficiency of the design process. It overcomes the problem of specified style difficulties in generating high-quality designs in traditional diffusion models. The research results indicated that: (1) the proposed method efficiently provides designers with diverse architectural designs; (2) new designs upon easily altered text prompts; (3) high scalability for designers to fine-tune it for applications in other design domains; and (4) an optimized architectural design workflow. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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