迈向AI-架构自由：深度学习虚拟架构设计与生成综述
Towards AI-Architecture Liberty: A Comprehensive Survey on Design and Generation of Virtual Architecture by Deep Learning
AI总结：
本文综述了深度学习在虚拟建筑设计中的应用，回顾149篇文献，总结挑战与四类方法，提出四个研究议程及交互促成因素，旨在促进设计师与AI协作。
摘要：
利用深度学习的3D形状生成技术引起了计算机视觉和建筑设计领域的广泛关注，有望丰富虚拟环境中的内容。然而，关于虚拟建筑设计的研究仍然有限，特别是在设计师与AI协作以及深度学习辅助设计方面。在我们的综述中，我们回顾了149篇相关文章（其中81.2%的文章发表于2019年至2023年），涵盖建筑设计、3D形状技术和虚拟环境。通过仔细审视文献，我们首先确定了虚拟建筑的原则，并阐明了其当前的生产挑战，包括数据集、多模态、设计直觉和生成框架。然后，我们介绍了利用3D形状生成来设计和生成虚拟建筑的最新方法，并总结了各种虚拟建筑方法的四个特征。基于我们的分析，我们阐述了四个研究议程，包括代理、沟通、用户考虑和工具集成。此外，我们强调了在深度学习辅助建筑生成中，与沉浸式系统进行普遍交互的四个重要促成因素。我们的工作有助于促进设计师与深度学习技术之间的理解，拓宽设计师与AI协作的途径。我们倡导跨学科努力来解决这一及时的研究课题，促进虚拟环境中的内容设计和生成。
英文摘要：
3D shape generation techniques leveraging deep learning have garnered significant interest from both the computer vision and architectural design communities, promising to enrich the content in the virtual environment. However, research on virtual architectural design remains limited, particularly regarding designer-AI collaboration and deep learning-assisted design. In our survey, we reviewed 149 related articles (81.2% of articles published between 2019 and 2023) covering architectural design, 3D shape techniques, and virtual environments. Through scrutinizing the literature, we first identify the principles of virtual architecture and illuminate its current production challenges, including datasets, multimodality, design intuition, and generative frameworks. We then introduce the latest approaches to designing and generating virtual buildings leveraging 3D shape generation and summarize four characteristics of various approaches to virtual architecture. Based on our analysis, we expound on four research agendas, including agency, communication, user consideration, and integrating tools. Additionally, we highlight four important enablers of ubiquitous interaction with immersive systems in deep learning-assisted architectural generation. Our work contributes to fostering understanding between designers and deep learning techniques, broadening access to designer-AI collaboration. We advocate for interdisciplinary efforts to address this timely research topic, facilitating content designing and generation in the virtual environment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
