DecoMind: A Generative AI System for Personalized Interior Design Layouts
Reema Alshehri, Rawan Alotaibi, Leen Almasri, and Rawan Altaweel

TL;DR
DecoMind is an AI system that generates personalized interior design layouts by combining user preferences with advanced generative models, ensuring realistic and aligned designs.
Contribution
The paper presents a novel AI system integrating CLIP, Stable Diffusion, and classifiers for automated, personalized interior design layout generation.
Findings
Successfully generates personalized interior layouts.
Ensures design alignment with user preferences.
Automates interior design process effectively.
Abstract
This paper introduces a system for generating interior design layouts based on user inputs, such as room type, style, and furniture preferences. CLIP extracts relevant furniture from a dataset, and a layout that contains furniture and a prompt are fed to Stable Diffusion with ControlNet to generate a design that incorporates the selected furniture. The design is then evaluated by classifiers to ensure alignment with the user's inputs, offering an automated solution for realistic interior design.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
