Automated Interior Room Design
Year: 2025
Type: article
Abstract: The goal of the "AI-Powered Interior Design Automation System" project is to transform interior design by meeting the demand for individualized, contemporary, and visually appealing space arrangements. The system processes and converts room photos into personalized designs by integrating cutting-edge AI technologies, including Transformer Models, U-Net Architecture, and Stable Diffusion. The solution improves design correctness and adaptability by utilizing the Transformer Model's contextual knowledge and the U-Net's feature extraction capabilities. By iteratively improving inputs, stable diffusion produces outputs that are incredibly stylized and lifelike. The technology incorporates real-time user inputs, like room images and stylistic choices, to enable customized designs that are suited to particular requirements. To guarantee design quality and relevance, a fine- tuning module modifies previously trained models using domain-specific datasets. Users may easily visualize and choose layouts thanks to an intuitive interface that shows created designs. The initiative offers creative, AI-driven solutions to create practical and fashionable interiors, representing a substantial development in design automation. This technology facilitates interior design creativity, efficiency, and customization by utilizing deep learning and user-centric design.
Authors: Affin K Shephy, Binil P Paul, Alen Yeldho, Jino James, Susanna M Santhosh
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7078131900
FWCI:
Cites:
Cited by:
Related to: