We address the challenge of generating 3D articulated objects in a controllable fashion. Currently, modeling articulated 3D objects is either achieved through laborious manual authoring, or using methods from prior work that are hard to scale and control directly. We leverage the interplay between part shape, connectivity, and motion using a denoising diffusion-based method with attention modules designed to extract correlations between part attributes. Our method takes an object category label and a part connectivity graph as input and generates an object's geometry and motion parameters. The generated objects conform to user-specified constraints on the object category, part shape, and part articulation. Our experiments show that our method outperforms the state-of-the-art in articulated object generation, producing more realistic objects while conforming better to user constraints. Video Summary at: http://youtu.be/cH_rbKbyTpE

翻译：我们以可控方式生成三维铰接物体为目标。当前，铰接三维物体的建模要么依赖费时的手工制作，要么使用难以规模化且难以直接控制的现有方法。我们利用一种基于去噪扩散的方法，该方法配备专为提取部件属性间相关性而设计的注意力模块，从而发挥部件形状、连接性和运动之间的相互作用。该方法以物体类别标签和部件连接图作为输入，并生成物体的几何参数与运动参数。生成的物体符合用户对物体类别、部件形状及部件铰接方式指定的约束条件。实验表明，该方法在铰接物体生成方面优于现有最先进技术，能够生成更逼真的物体，同时更好地符合用户约束。视频摘要请见：http://youtu.be/cH_rbKbyTpE