SceneHGN:为精细粒度几何形状的3D室内场景生成的等级图形网络
IEEE transactions on pattern analysis and machine intelligence
|October 11, 2023
概括
通过使用层次图形网络,SceneHGN直接生成3D室内场景,包括家具几何和布局. 这种方法整合了房间,物体和部分层面,用于全面的场景合成.
科学领域:
- 计算机图形 计算机图形
- 人工智能的人工智能
- 计算几何学的计算几何学
背景情况:
- 3D室内场景对于游戏和VR等应用至关重要.
- 手动创建高质量的3D场景耗时且需要专业知识.
- 现有的方法部分地解决场景生成,单独关注房间布局或对象几何.
研究的目的:
- 提出一种用于直接,端到端生成可信的3D室内场景的新方法.
- 将房间布局,物体细节及其空间关系整合到一个统一的框架中.
- 克服现有的部分场景生成方法的局限性.
主要方法:
- SceneHGN是一个层次图形网络,可以模拟3D室内场景,从房间到对象的部分层次.
- 功能区域被引入为中间表示,以管理复杂性.
- 基于条件递归神经网络 (RvNN) 的变异自编码器 (VAE) 产生场景内容.
主要成果:
- SceneHGN直接生成完整的3D室内场景,具有细粒度的对象几何和布局.
- 层次的图表表现有效地捕捉了层次间和层次内部的关系.
- 实验结果显示,与现有的部分方法相比,发电质量优越.
结论:
- SceneHGN为3D室内场景合成提供了统一的方法,同时解决布局和几何.
- 该方法在生成详细和可信的3D室内环境方面表现出有效性.
- SceneHGN是多功能,支持诸如场景编辑,插值和从任意边界生成等应用程序.
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