Landscape renderings are realistic images of landscape sites, allowing stakeholders to perceive better and evaluate design ideas. While recent advances in Generative Artificial Intelligence (GAI) enable automated generation of landscape renderings, the end-to-end methods are not compatible with common design processes, leading to insufficient alignment with design idealizations and limited cohesion of iterative landscape design. Informed by a formative study for comprehending design requirements, we present PlantoGraphy, an iterative design system that allows for interactive configuration of GAI models to accommodate human-centered design practice. A two-stage pipeline is incorporated: first, concretization module transforms conceptual ideas into concrete scene layouts with a domain-oriented large language model; and second, illustration module converts scene layouts into realistic landscape renderings using a fine-tuned low-rank adaptation diffusion model. PlantoGraphy has undergone a series of performance evaluations and user studies, demonstrating its effectiveness in landscape rendering generation and the high recognition of its interactive functionality.

翻译：景观渲染是景观场地的逼真图像，能够帮助利益相关者更好地感知和评估设计构想。尽管生成式人工智能的近期进展实现了景观渲染的自动生成，但端到端方法与传统设计流程不兼容，导致与设计理想化的对齐不足，且迭代景观设计的连贯性有限。基于对设计需求理解的形成性研究，我们提出了PlantoGraphy——一种迭代设计系统，允许对GAI模型进行交互式配置，以适配以人为中心的设计实践。该系统采用两阶段流水线：首先，具体化模块通过领域导向的大语言模型将概念性构想转化为具体的场景布局；其次，插图模块利用微调的低秩自适应扩散模型将场景布局转化为逼真的景观渲染。PlantoGraphy经过一系列性能评估与用户研究，证明了其在景观渲染生成中的有效性及其交互功能的高度认可性。