摘要
人工智能(AI)图像生成技术正在改变景观设计中的传统工作模式,其中,“图生图”式生成对抗网络(generative adversarial network,GAN)技术具备辅助方案设计的潜能,因此面向用户端对其展开技术适用性评价研究对于优化工具选择、提升设计效率尤为重要。本研究旨在借助图像分析和用户调查方法,评估GAN生成方法生成结果的质量、与设计工作对接的有效性,以及景观设计师对图像生成结果的接受度。研究以Pix2Pix–Bicycle GAN工作流中布局生成与平面渲染两项任务为评价对象,建立了基于地块数量的绝对/欧式距离、直方图距离、结构相似性指数等图像分析指标;针对GAN生成结果的视觉真实性和色彩肌理偏好开展了两项在线用户问卷调查。结果显示,GAN生成布局与真实布局相似性高,GAN渲染平面能够满足概念方案呈现要求、用户接受度好。最后,本文探讨了GAN生成方法的内在合理性及其在行业伦理及数据偏见方面的局限性,反思现阶段连接AI辅助设计与循证设计之间的技术空缺。
Artificial intelligence(AI)image generation is revolutionizing traditional workflow in landscape architecture industry,among which the“image-to-image”generative adversarial network(GAN)exhibits potential to facilitate concept design.Therefore,it underscores the importance of applicability evaluation from the perspective of users.This research aims to evaluate the quality of the GAN-generated results,their effectiveness in integrating with design workflows,and the landscape architects'acceptance of the results through image analysis and user survey.The evaluation focuses on layout generation and masterplan rendering within the Pix2Pix–Bicycle GAN workflow.The evaluation metrics of image analysis including block number absolute/Euclidean distance,histogram distance,and structural similarity index measure,were employed.Additionally,the online survey with two questionnaires was conducted to evaluate the visual realism and preference for color and texture of the GAN-generated results.The findings indicate that the GAN-generated layout exhibits a high similarity to the human-designed layout,and the GAN-rendered masterplans fulfill the criteria for concept design and garner positive user acceptance.Conclusively,this study delves into the intrinsic rationality of the GAN generation methods and limitations in professional ethics and data bias,reflecting on the gaps between current AI-assisted design methods and evidence-based design.
作者
周怀宇
向双斌
Huaiyu ZHOU;Shuangbin XIANG(Department of Architecture,School of Architecture and Planning,Hunan University,Changsha 410082,China;Department of Landscape Architecture,School of Architecture,Tsinghua University,Beijing 100084,China;Landscape Architecture Studio,Beijing General Municipal Engineering Design&Research Institute Co.,Ltd.,Beijing 100088,China)
出处
《景观设计学（中英文）》
CSCD
2024年第2期58-73,共16页
Landscape Architecture Frontiers
关键词
景观设计学
图像生成
生成对抗网络
人工智能辅助设计
适用性评价
景观平面
Landscape Architecture
Image Generation
Generative Adversarial Network
Artificial Intelligence-Assisted Design
Applicability Evaluation
Landscape Masterplan
