arXiv:2508.17832cs.CV2025-08被引 5

提出分层布局生成方法,精细构建3D室内场景。

HLG: Comprehensive 3D Room Construction via Hierarchical Layout Generation

  • 采用自粗到细的分层结构,分解复杂场景为多级布局。
  • 通过可训练优化网络解决物体错位、重叠等问题。
  • 适合虚拟现实、智能体导航等需高精度3D环境的应用。

真实感3D室内场景生成对虚拟现实、室内设计、具身智能和场景理解至关重要。现有方法虽在家具整体布局上取得进展,但难以捕捉细粒度物体摆放,限制了生成环境的真实性和实用性,制约了沉浸式体验与具身AI的场景理解。为此,我们提出分层布局生成(HLG)方法,首次采用自粗到细的层次化策略,从大尺度家具布置逐步细化至精细物体排列。具体而言,其细粒度布局对齐模块通过垂直与水平解耦,将复杂3D室内场景分解为多个粒度层级。此外,可训练的布局优化网络有效解决定位错误、朝向偏差和物体交叠等问题,确保场景结构一致且物理合理。大量实验表明,该方法在生成逼真室内场景方面优于现有方法。本工作推动了场景生成领域的发展,为需要详细3D环境的应用开辟新可能。代码将于发表后开源,以促进后续研究。

原文摘要 · Abstract (English)

Realistic 3D indoor scene generation is crucial for virtual reality, interior design, embodied intelligence, and scene understanding. While existing methods have made progress in coarse-scale furniture arrangement, they struggle to capture fine-grained object placements, limiting the realism and utility of generated environments. This gap hinders immersive virtual experiences and detailed scene comprehension for embodied AI applications. To address these issues, we propose Hierarchical Layout Generation (HLG), a novel method for fine-grained 3D scene generation. HLG is the first to adopt a coarse-to-fine hierarchical approach, refining scene layouts from large-scale furniture placement to intricate object arrangements. Specifically, our fine-grained layout alignment module constructs a hierarchical layout through vertical and horizontal decoupling, effectively decomposing complex 3D indoor scenes into multiple levels of granularity. Additionally, our trainable layout optimization network addresses placement issues, such as incorrect positioning, orientation errors, and object intersections, ensuring structurally coherent and physically plausible scene generation. We demonstrate the effectiveness of our approach through extensive experiments, showing superior performance in generating realistic indoor scenes compared to existing methods. This work advances the field of scene generation and opens new possibilities for applications requiring detailed 3D environments. We will release our code upon publication to encourage future research.

3D生成场景重建分层建模

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