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首次观测 · 记录 #1CVF · CVPR 2026:cvf:f5c5b76925bae2d1591e2ebe6bd82c85CVF · CVPR 2026

Artiverse: A Diverse and Physically Grounded Dataset for Articulated Objects

Iliash, Denys, Liu, Jiayi, Fokin, Egor, Wu, Qirui, Amiri, Ali Mahdavi, Savva, Manolis, Chang, Angel X.

原文摘要

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 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.

cs.CV

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition · 2026 · 正式发表