FlexPlan: High-flexibility interactive floorplan design based on ArchiGraph

IF 1.8 4区 计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Graphical Models Pub Date : 2025-12-01 Epub Date: 2025-11-05 DOI:10.1016/j.gmod.2025.101303
Zhan Wang , Junhao Wang , Zongpu Li , Hao Su , Pei Lv , Mingliang Xu
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引用次数: 0

Abstract

AI-aided floorplan design is a longstanding task in computer graphics. However, most of the existing methods focus on generating floorplans by limited architecture-level elements (e.g., room sizes, positions, and adjacencies), which ignore environmental factors and do not support customized designs. In this paper, we propose FlexPlan, an interactive approach for high-flexibility floorplan design. In FlexPlan, we propose a novel graph structure, named ArchiGraph, which enables flexible editing more comprehensive layout elements (e.g., architectures, environments, human needs) in a floorplan. First, we match similar floorplans according to the input architecture and environment features. Then, leveraging ArchiGraph, we interactively produce rooms’ attributes and quickly output the vectorized floorplans. For ArchiGraph, we design a RelationNet to predict room adjacencies, and propose a BoxNet to generate high-quality room boxes. Subjective and objective experiments show that our method is compatible with generating diverse complex floorplans (e.g., floorplans with irregular layout boundaries and room shapes). Compared with the state-of-the-art methods, our method can produce higher quality floorplans, and increase the speed of layout generation by nearly 20 times at most.

Abstract Image

FlexPlan:基于ArchiGraph的高灵活性交互式平面图设计
人工智能辅助平面图设计是计算机图形学中一项长期存在的任务。然而,大多数现有的方法侧重于通过有限的建筑级元素(例如,房间大小,位置和邻接关系)生成平面图,这忽略了环境因素,不支持定制设计。在本文中,我们提出了FlexPlan,一种用于高灵活性平面设计的交互式方法。在FlexPlan中,我们提出了一种新的图形结构,称为ArchiGraph,它可以在平面图中灵活地编辑更全面的布局元素(例如,建筑,环境,人的需求)。首先,我们根据输入的建筑和环境特征匹配相似的平面图。然后,利用ArchiGraph,我们交互地生成房间的属性,并快速输出矢量化的平面图。对于ArchiGraph,我们设计了一个RelationNet来预测房间邻接关系,并提出了一个BoxNet来生成高质量的房间盒子。主观和客观实验表明,我们的方法可以生成各种复杂的平面布置图(如不规则布局边界和房间形状的平面布置图)。与现有的方法相比,我们的方法可以生成更高质量的平面布置图,并将平面布置图生成速度最多提高近20倍。
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来源期刊
Graphical Models
Graphical Models 工程技术-计算机:软件工程
CiteScore
3.60
自引率
5.90%
发文量
15
审稿时长
47 days
期刊介绍: Graphical Models is recognized internationally as a highly rated, top tier journal and is focused on the creation, geometric processing, animation, and visualization of graphical models and on their applications in engineering, science, culture, and entertainment. GMOD provides its readers with thoroughly reviewed and carefully selected papers that disseminate exciting innovations, that teach rigorous theoretical foundations, that propose robust and efficient solutions, or that describe ambitious systems or applications in a variety of topics. We invite papers in five categories: research (contributions of novel theoretical or practical approaches or solutions), survey (opinionated views of the state-of-the-art and challenges in a specific topic), system (the architecture and implementation details of an innovative architecture for a complete system that supports model/animation design, acquisition, analysis, visualization?), application (description of a novel application of know techniques and evaluation of its impact), or lecture (an elegant and inspiring perspective on previously published results that clarifies them and teaches them in a new way). GMOD offers its authors an accelerated review, feedback from experts in the field, immediate online publication of accepted papers, no restriction on color and length (when justified by the content) in the online version, and a broad promotion of published papers. A prestigious group of editors selected from among the premier international researchers in their fields oversees the review process.
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