InSpace: Structure-Aware 3D Indoor Scene Generation from a Single 360° Image

Recent advances in single image-to-3D generation have en-abled high-quality asset synthesis, yet extending these capabilities toindoor scene generation remains challenging. Existing methods focus onasset-level generation while neglecting the structural layout, which isessential for downstream applications and serves as the spatial anchorfor grounding assets. However, a single image with a limited field ofview lacks the spatial coverage to recover a coherent global layout. Tothis end, we use a 360° image represented in equirectangular projec-tion (ERP) and propose InSpace, a structure-aware framework for 3Dindoor scene generation. InSpace comprises three stages: (1) estimat-ing partial scene geometry as spatial priors, (2) generating coarse scene* †Work done during an internship at NAVER LABS. Co-corresponding authorsArtifactsMisplacementMisplacementERP Image ERP ImageInput Result Floating Input Result ResultResultSceneGen SAM3D InSpace (Ours)(a) Current Single Image to 3D Scene Generation (b) ERP Image to 3D Scene GenerationFig. 2: (a) Existing single-image methods generate individual assets without structurallayout, causing floating, misplacement, and artifacts. (b) InSpace uses an ERP imageto generate complete indoor scenes with structural layout and well-grounded assets.structure with view-selective cross-attention, and (3) producing detailedlayout and asset geometry with textures through a global-local hybridattention, using flow matching. We also propose ERP-FRONT, a pairedERP-Image-to-3D indoor scene dataset based on 3D-FRONT. Exper-iments show that InSpace generates complete 3D indoor scenes withstructural layout, along with separate textured assets from a single ERPimage, achieving strong performance across 3D and 2D metrics.