Exploring Text-based Realistic Building Facades Editing Applicaiton

Fuente: arXiv
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Autores principales: Wang, Jing, Zhang, Xin
Formato: Preprint
Publicado: 2024
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author Wang, Jing
Zhang, Xin
author_facet Wang, Jing
Zhang, Xin
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2405_02967
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Exploring Text-based Realistic Building Facades Editing Applicaiton
Wang, Jing
Zhang, Xin
Human-Computer Interaction
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.
title Exploring Text-based Realistic Building Facades Editing Applicaiton
topic Human-Computer Interaction
url https://arxiv.org/abs/2405.02967