{"ID":2879232,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.16696","arxiv_id":"2508.16696","title":"DecoMind: A Generative AI System for Personalized Interior Design Layouts","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.","short_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 incorp...","url_abs":"https://arxiv.org/abs/2508.16696","url_pdf":"https://arxiv.org/pdf/2508.16696v1","authors":"[\"Reema Alshehri\",\"Rawan Alotaibi\",\"Leen Almasri\",\"Rawan Altaweel\"]","published":"2025-08-22T00:01:48Z","proceeding":"cs.GR","tasks":"[\"cs.GR\",\"cs.AI\"]","methods":"[\"Diffusion Model\"]","has_code":false}