Journal of Engineering, Project, and Production Management, 2026, 16(6), 2025-365
An Interior Intelligent Design System Based on GAN and 3D Scene Automatic Generation Technology
Lecturer, School of Urban Construction, Luoyang Polytechnic, Luoyang, 471000, China, E-mail: cbply613@126.com
Project Management
Received December 30, 2025; revised February 10, 2026; July 28, 2026; accepted September 7, 2026
Available online September 20, 2026
Abstract: To address the inefficiencies, high costs, and limitations in spatial rationality and automation prevalent in traditional and existing intelligent interior design approaches, this study proposes and implements an end-to-end intelligent interior design system. The system integrates a deep convolutional Generative Adversarial Network (GAN) for automated floor plan layout generation with an automatic 3D scene generation module, facilitating a seamless transition from 2D layouts to immersive 3D visualizations. The proposed GAN model incorporates class-aware convolutional layers and a spatial constraint loss function to enhance layout rationality and diversity. Experiments demonstrate that the proposed method achieves high layout accuracy (96.78%) and low furniture overlap (7.28%) on public datasets, while maintaining robust 3D reconstruction accuracy (84.36%) and precise model alignment. System performance tests show real-time rendering capability under concurrent user loads. This research provides an efficient automated solution that enhances design productivity, supports visual decision-making, and offers practical value for project management in interior design applications.
Keywords: Intelligent interior design; generative adversarial network (GAN); 3D scene generation technology; automation system; layout method.
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Citation: Cheng, B. (2026). An Interior Intelligent Design System Based on GAN and 3D Scene Automatic Generation Technology. Journal of Engineering, Project, and Production Management, 16(6), 2025-365.
