HSM: Hierarchical Scene Motifs for Multi-Scale Indoor Scene Generation
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915654980861952 |
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| author | Pun, Hou In Derek Tam, Hou In Ivan Wang, Austin T. Huo, Xiaoliang Chang, Angel X. Savva, Manolis |
| author_facet | Pun, Hou In Derek Tam, Hou In Ivan Wang, Austin T. Huo, Xiaoliang Chang, Angel X. Savva, Manolis |
| contents | 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 . |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_16848 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | HSM: Hierarchical Scene Motifs for Multi-Scale Indoor Scene Generation Pun, Hou In Derek Tam, Hou In Ivan Wang, Austin T. Huo, Xiaoliang Chang, Angel X. Savva, Manolis Graphics Computer Vision and Pattern Recognition 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 . |
| title | HSM: Hierarchical Scene Motifs for Multi-Scale Indoor Scene Generation |
| topic | Graphics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2503.16848 |