Articulate AnyMesh：开放词汇 3D 铰接物体建模
Articulate AnyMesh: Open-Vocabulary 3D Articulated Objects Modeling
AI总结：
本文提出 Articulate AnyMesh 框架，利用视觉-语言模型和视觉提示从任意刚性 3D 网格生成开放词汇的高质量铰接物体，并验证其可扩展数据集及支持机器人操作技能迁移。
摘要：
3D 铰接物体建模长期以来一直是一个具有挑战性的问题，因为它既需要捕捉准确的表面几何，又需要捕捉具有语义意义且空间精确的结构、部件和关节。现有方法严重依赖来自有限手工铰接物体类别（例如柜子和抽屉）的训练数据，这限制了它们在开放词汇场景中对广泛铰接物体进行建模的能力。为解决这些局限，我们提出 Articulate AnyMesh，这是一个能够以开放词汇方式将任意刚性 3D 网格转换为其对应铰接版本的自动化框架。给定一个 3D 网格，我们的框架利用先进的视觉-语言模型和视觉提示技术提取语义信息，从而同时实现物体部件分割和功能性关节构建。实验表明，Articulate AnyMesh 能够生成大规模、高质量的 3D 铰接物体，包括工具、玩具、机械设备和车辆，显著扩展了现有 3D 铰接物体数据集的覆盖范围。此外，我们表明这些生成的资产能够促进在仿真中获取新的铰接物体操作技能，随后这些技能可迁移到真实机器人系统。我们的 GitHub 网站是 https://articulate-anymesh.github.io。
英文摘要：
3D articulated objects modeling has long been a challenging problem, since it requires to capture both accurate surface geometries and semantically meaningful and spatially precise structures, parts, and joints. Existing methods heavily depend on training data from a limited set of handcrafted articulated object categories (e.g., cabinets and drawers), which restricts their ability to model a wide range of articulated objects in an open-vocabulary context. To address these limitations, we propose Articulate Anymesh, an automated framework that is able to convert any rigid 3D mesh into its articulated counterpart in an open-vocabulary manner. Given a 3D mesh, our framework utilizes advanced Vision-Language Models and visual prompting techniques to extract semantic information, allowing for both the segmentation of object parts and the construction of functional joints. Our experiments show that Articulate Anymesh can generate large-scale, high-quality 3D articulated objects, including tools, toys, mechanical devices, and vehicles, significantly expanding the coverage of existing 3D articulated object datasets. Additionally, we show that these generated assets can facilitate the acquisition of new articulated object manipulation skills in simulation, which can then be transferred to a real robotic system. Our Github website is https://articulate-anymesh.github.io.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
