GRCVMar 21, 2025

HSM: Hierarchical Scene Motifs for Multi-Scale Indoor Scene Generation

arXiv:2503.16848v211 citationsh-index: 46
Originality Incremental advance
AI Analysis

This addresses the problem of generating realistic, dense indoor scenes for applications like virtual reality and interior design, though it appears incremental as it builds on hierarchical scene understanding.

The paper tackles the problem of generating dense indoor 3D scenes with realistic small object arrangements, which existing methods often neglect or place randomly. HSM outperforms existing methods by better conforming to user input across room types and spatial configurations.

Despite advances in indoor 3D scene layout generation, synthesizing scenes with dense object arrangements remains challenging. Existing methods focus on large furniture while neglecting smaller objects, resulting in unrealistically empty scenes. Those that place small objects typically do not honor arrangement specifications, resulting in largely random placement not following the text description. We present Hierarchical Scene Motifs (HSM): a hierarchical framework for indoor scene generation with dense object arrangements across spatial scales. Indoor scenes are inherently hierarchical, with surfaces supporting objects at different scales, from large furniture on floors to smaller objects on tables and shelves. HSM embraces this hierarchy and exploits recurring cross-scale spatial patterns to generate complex and realistic scenes in a unified manner. Our experiments show that HSM outperforms existing methods by generating scenes that better conform to user input across room types and spatial configurations. Project website is available at https://3dlg-hcvc.github.io/hsm .

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