Using Artificial Intelligence to Transform Sketches into Realistic Visualizations of Iconic Buildings

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Fatmanur Atalay

Abstract

The sketch phase in architectural design is a process where design requirements are not fully defined, but decisions regarding the architectural product largely become clear. The integration of artificial intelligence (AI) into this process can be considered an exploration of potential design products that address early-stage design decisions. This paper examines how AI technologies can be utilized in the field of architecture, starting from the sketch phase and continuing through 3D visualization and rendering processes. Inspired by the sketches of pioneering modernist architects, the aim is to demonstrate how “sketch-to-sketch rendering” and “sketch-to-3D rendering” can be produced using AI-based tools. Based on the selected sketches by well-known architects and actual visuals of the buildings as references, prompts obtained from ChatGPT were used to generate sketch-to-sketch and sketch-to-3D render visuals in the artificial intelligence tools Air for SketchUp and Leonardo AI, and the results are compared. The applications demonstrate that Air for SketchUp provides more realistic and visually successful results, especially in the 3D rendering phase. Leonardo AI was notable for its capacity to generate quick alternatives that are more experimental and artistic in nature. However, these outputs tend to show weaker ties to architectural context. The findings suggest that human-machine collaboration can offer new potential in architectural design processes and that artificial intelligence tools can transform the traditional sketch process, taking on a supportive role for designers. It was determined that AI tools can contribute to architectural design processes in terms of creativity, reflecting environmental context in design, and developing design ideas.

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Atalay, F. (2025). Using Artificial Intelligence to Transform Sketches into Realistic Visualizations of Iconic Buildings. Journal of Architectural/Planning Research and Studies (JARS), 23(1), Article 276270. https://doi.org/10.56261/jars.v23.276270
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