AI RESEARCH
Code-as-Room: Generating 3D Rooms from Top-Down View Images via Agentic Code Synthesis
arXiv CS.CV
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ArXi:2605.18451v1 Announce Type: new Designing realistic and functional 3D indoor rooms is essential for a wide range of applications, including interior design, virtual reality, gaming, and embodied AI. While recent MLLM-based approaches have shown great potential for 3D room synthesis from textual descriptions or reference images, text-based methods struggle to capture precise spatial information, and existing image-conditioned agents suffer from instability and infinite looping when tasked with holistic room generation from top-down views.