构建5400个带物理属性的可动3D物体数据集，助力真实交互建模。
Artiverse: A Diverse and Physically Grounded Dataset for Articulated Objects
- 人工设计+半自动标注，高效生成高精度可动物体
- 涵盖88类、5400个物体，含多自由度关节与物理属性
- 适合做机器人交互、虚拟现实和功能理解研究
我们提出Artiverse，一个包含5400个由人类创作的高质量可动3D物体的多样化且具有物理基础的数据集，用于真实的功能建模与仿真。数据集覆盖88个类别，源自多个3D静态资源库。每个物体均标注功能部件、内部结构、真实的运动学关系与可动关节（包括多自由度关节），以及尺寸、材质、质量等物理属性。我们开发了结合少样本分割、几何推理与多阶段人工验证的半自动化标注流程，使人工标注时间减少超30%。我们在部件运动性分析、可动物体生成及基于物理的交互任务上验证了Artiverse的价值。该数据集为推进可动物体的功能理解提供了重要资源。
原文摘要 · Abstract (English)
We present Artiverse, a diverse and physically grounded dataset of high-quality articulated 3D objects designed for realistic functional modeling and simulation. Artiverse contains 5.4K human-authored objects across a broad range of 88 categories, aggregated from multiple 3D static repositories. Objects are annotated with functional parts, interior structures, realistic kinematic relationships and articulated joints including multi-DoF joints, and physical attributes such as metric scale, material, and mass. We develop a semi-automated annotation pipeline that combines few-shot segmentation, geometric reasoning, and multi-stage human verification to achieve high-quality and efficient annotation, reducing manual annotation time by over 30%. We demonstrate the value of Artiverse on tasks of part mobility analysis, articulated object generation, and physics-based interaction. Artiverse provides a data resource to advance functional understanding for articulated objects.
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