CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

PDF papers
References
id acadia23_v2_616
authors Kuang, Zheyuan; Zhang, Jiaxin; Huang, Yiying; Li, Yunqin
year 2023
title Advancing Urban Renewal: An Automated Approach to Generating Historical Arcade Facades with Stable Diffusion Models
source ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 616-625.
summary Urban renewal and transformation processes necessitate the preservation of the histor- ical urban fabric, particularly in districts known for their architectural and historical significance. These regions, with their diverse architectural styles, have traditionally required extensive preliminary research, often leading to subjective results. However, the advent of machine learning models has opened up new avenues for generating building facade images. Despite this, creating high-quality images for historical district renovations remains challenging, due to the complexity and diversity inherent in such districts. In response to these challenges, our study introduces a new methodology for automatically generating images of historical arcade facades, utilizing Stable Diffusion models conditioned on textual descriptions. By classifying and tagging a variety of arcade styles, we have constructed several realistic arcade facade image datasets. We trained multiple low-rank adaptation (LoRA) models to control the stylistic aspects of the gener- ated images, supplemented by ControlNet models for improved precision and authenticity. Our approach has demonstrated high levels of precision, authenticity, and diversity in the generated images, showing promising potential for real-world urban renewal projects. This new methodology offers a more efficient and accurate alternative to conventional design processes in urban renewal, bypassing issues of unconvincing image details, lack of precision, and limited stylistic variety. Future research could focus on integrating this two-dimensional image generation with three-dimensional modeling techniques, providing a more comprehensive solution for renovating architectural facades in historical districts.
series ACADIA
type paper
email
full text file.pdf (3,303,770 bytes)
references Content-type: text/plain
Details Citation Select
100%; open Cheng Sun, Yiran Zhou, and Yunsong Han (2022) Find in CUMINCAD Automatic Generation of Architecture Facade for Historical Urban Renovation Using Generative Adversarial Network , Building and Environment 212 (March): 108781. doi:10.1016/j.buildenv.2022.108781

100%; open Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen (2021) Find in CUMINCAD LoRA: Low-Rank Adaptation of Large Language Models , arXiv. doi:10.48550/arXiv.2106.09685

100%; open Haoran Ma (2023) Find in CUMINCAD Text Semantics to Image Generation: A Method of Building Facades Design Base on Stable Diffusion Model , arXiv. doi:10.48550/arXiv.2303.12755

100%; open Lvmin Zhang and Maneesh Agrawala (2023) Find in CUMINCAD Adding Conditional Control to Text-to-Image Diffusion Models , arXiv. http://arxiv.org/abs/2302.05543

100%; open Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman (2023) Find in CUMINCAD DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation , arXiv. http://arxiv.org/abs/2208.12242

100%; open Qiu Yu, Jamal Malaeb, and Wenjun Ma (2020) Find in CUMINCAD Architectural Facade Recognition and Generation through Generative Adversarial Networks , 2020 International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE), 310–16. doi:10.1109/ICBASE51474.2020.00072

100%; open Tomas Vivanco Larrain, Antonia Valencia, and Philip F. Yuan (2021) Find in CUMINCAD SPATIAL FINDINGS ON CHILEAN ARCHITECTURE STYLEGAN AI GRAPHICS , CAADRIA 2021: Projections

100%; open Xiaohong Tan and Uwe Altrock (2016) Find in CUMINCAD Struggling for an Adaptive Strategy? Discourse Analysis of Urban Regeneration Processes – A Case Study of Enning Road in Guangzhou City , Habitat International 56 (August): 245–57. doi:10.1016/j.habitatint.2016.06.006

100%; open Ye Yu and William A. P. Smith (2021) Find in CUMINCAD Outdoor Inverse Rendering from a Single Image Using Multiview Self-Supervision , arXiv. http://arxiv.org/abs/2102.06591

last changed 2024/12/20 09:13
pick and add to favorite papersHOMELOGIN (you are user _anon_712458 from group guest) CUMINCAD Papers Powered by SciX Open Publishing Services 1.002