| id |
ecaade2024_57 |
| authors |
Bank, Mathias; Schlusche, Johannes; Rasoulzadeh, Shervin; Schinegger, Kristina; Rutzinger, Stefan |
| year |
2024 |
| title |
Diffused Tomography - Design ideation on architectural models through image sequences |
| source |
Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 537–546 |
| doi |
https://doi.org/10.52842/conf.ecaade.2024.2.537
|
| summary |
The paper outlines a novel methodology for applying AI-driven style transfer to complex 3D architectural models. It involves a sequential process of slicing, training, video-guided diffusion, and reconstruction to transform existing 3D models based on textual descriptions into new stylistic forms. This approach enables architects to explore diverse design concepts, focusing on spatial composition, visual appearance, and tectonics. The results demonstrate the potential of AI in enhancing early-stage design ideation, offering new perspectives on interior-exterior relationships in architecture through AI-generated 3D models. |
| keywords |
AI, Video Diffusion, Architectural Design, Form finding, Concept model, Ideation |
| series |
eCAADe |
| email |
|
| full text |
 file.pdf (793,974 bytes) |
| references |
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