AI-Driven Explorations: Reference-Guided Synthesis

This project leverages a stable diffusion-based pipeline enhanced by reference-driven control networks for edge and depth detection. By anchoring each iteration to consistent geometric and spatial cues, the workflow transcends purely style-based prompting, preserving the core design intent throughout the generative process.

Compared to conventional methods, this approach significantly reduces iteration time—from days or weeks down to minutes—while retaining a reliable framework for design exploration. The result is a more precise, repeatable system that still harnesses the inherent flexibility of diffusion-based generative AI, enabling rapid yet controlled experimentation with architectural concepts.