MagicArticulate：讓您的3D模型具備關節可動性

MagicArticulate: Make Your 3D Models Articulation-Ready

February 17, 2025

作者: Chaoyue Song, Jianfeng Zhang, Xiu Li, Fan Yang, Yiwen Chen, Zhongcong Xu, Jun Hao Liew, Xiaoyang Guo, Fayao Liu, Jiashi Feng, Guosheng Lin

cs.AI

摘要

隨著三維內容創作的爆炸式增長，對於將靜態三維模型自動轉換為支持逼真動畫的關節化版本的需求日益增加。傳統方法嚴重依賴於手動標註，這既耗時又耗力。此外，大規模基準數據集的缺乏阻礙了基於學習的解決方案的發展。在本研究中，我們提出了MagicArticulate，這是一個有效的框架，能夠自動將靜態三維模型轉化為關節化資源。我們的主要貢獻有三方面。首先，我們引入了Articulation-XL，這是一個大規模基準數據集，包含超過33,000個帶有高質量關節標註的三維模型，這些模型是從Objaverse-XL中精心挑選的。其次，我們提出了一種新穎的骨架生成方法，將該任務表述為序列建模問題，利用自迴歸變換器來自然處理骨架中不同數量的骨骼或關節及其在不同三維模型之間的固有依賴關係。第三，我們使用功能性擴散過程來預測蒙皮權重，該過程結合了頂點與關節之間的體積測地距離先驗。大量實驗表明，MagicArticulate在多樣化的物體類別上顯著優於現有方法，實現了能夠支持逼真動畫的高質量關節化。項目頁面：https://chaoyuesong.github.io/MagicArticulate。

English

With the explosive growth of 3D content creation, there is an increasing demand for automatically converting static 3D models into articulation-ready versions that support realistic animation. Traditional approaches rely heavily on manual annotation, which is both time-consuming and labor-intensive. Moreover, the lack of large-scale benchmarks has hindered the development of learning-based solutions. In this work, we present MagicArticulate, an effective framework that automatically transforms static 3D models into articulation-ready assets. Our key contributions are threefold. First, we introduce Articulation-XL, a large-scale benchmark containing over 33k 3D models with high-quality articulation annotations, carefully curated from Objaverse-XL. Second, we propose a novel skeleton generation method that formulates the task as a sequence modeling problem, leveraging an auto-regressive transformer to naturally handle varying numbers of bones or joints within skeletons and their inherent dependencies across different 3D models. Third, we predict skinning weights using a functional diffusion process that incorporates volumetric geodesic distance priors between vertices and joints. Extensive experiments demonstrate that MagicArticulate significantly outperforms existing methods across diverse object categories, achieving high-quality articulation that enables realistic animation. Project page: https://chaoyuesong.github.io/MagicArticulate.