  This paper explores the utilization of diffusion models and textual guidance
for achieving localized editing of building facades, addressing the escalating
demand for sophisticated editing methodologies in architectural design and
urban planning. Leveraging the robust generative capabilities of diffusion
models, this study presents a promising avenue for realistically synthesizing
and modifying architectural facades. Through iterative diffusion and text
descriptions, these models adeptly capture both the intricate global and local
structures inherent in architectural facades, thus effectively navigating the
complexity of such designs. Additionally, the paper examines the expansive
potential of diffusion models in various facets, including the generation of
novel facade designs, the enhancement of existing facades, and the realization
of personalized customization. Despite their promise, diffusion models
encounter obstacles such as computational resource constraints and data
imbalances. To address these challenges, the study introduces the innovative
Blended Latent Diffusion method for architectural facade editing, accompanied
by a comprehensive visual analysis of its viability and efficacy. Through these
endeavors, we aims to propel forward the field of architectural facade editing,
contributing to its advancement and practical application.
