无需参考抓握，生成真实3D双手操作物体动画
BimArt: A Unified Approach for the Synthesis of 3D Bimanual Interaction with Articulated Objects
- 用关节感知特征生成接触图，捕捉双手协作模式
- 在多个数据集上运动质量与多样性均超越现有方法
- 适合虚拟人交互、动画制作等需要自然双手动作的场景
我们提出BimArt，一种统一生成3D双手操作可动物体的新方法。不同于以往依赖参考抓握、粗略手部轨迹或分阶段处理抓握与操作的工作，BimArt通过关节感知特征表示，基于物体运动轨迹生成基于距离的接触图，揭示丰富的双手协作模式。学习到的接触先验用于引导手部运动生成器，产出多样且逼真的双手运动，实现物体移动与操作。实验表明，该方法在高维复杂双手-物体交互空间中有效建模，显著提升动画质量与多样性，优于当前最优方案。项目页面：https://vcai.mpi-inf.mpg.de/projects/bimart/
原文摘要 · Abstract (English)
We present BimArt, a novel generative approach for synthesizing 3D bimanual hand interactions with articulated objects. Unlike prior works, we do not rely on a reference grasp, a coarse hand trajectory, or separate modes for grasping and articulating. To achieve this, we first generate distance-based contact maps conditioned on the object trajectory with an articulation-aware feature representation, revealing rich bimanual patterns for manipulation. The learned contact prior is then used to guide our hand motion generator, producing diverse and realistic bimanual motions for object movement and articulation. Our work offers key insights into feature representation and contact prior for articulated objects, demonstrating their effectiveness in taming the complex, high-dimensional space of bimanual hand-object interactions. Through comprehensive quantitative experiments, we demonstrate a clear step towards simplified and high-quality hand-object animations that surpass the state of the art in motion quality and diversity. Project page: https://vcai.mpi-inf.mpg.de/projects/bimart/.
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