Artiverse: A Diverse and Physically Grounded Dataset for Articulated Objects 文章

ArXiv CS.CV2026-05-26NEWSen作者: Denys Iliash, Jiayi Liu, Egor Fokin, Qirui Wu, Ali Mahdavi-Amiri, Manolis Savva, Angel X. Chang

摘要

arXiv:2605.24403v1 Announce Type: new Abstract: 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.

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