无需物体先验，实现手物交互的动态4D高斯溅射重建。
Interaction-Aware 4D Gaussian Splatting for Dynamic Hand-Object Interaction Reconstruction
- 引入可优化参数的交互感知高斯，提升结构清晰度。
- 融合手形信息到物体形变场，建模灵活运动与物理交互。
- 渐进式优化策略+显式正则化，稳定动态重建过程。
本文聚焦于无物体先验条件下，同时建模手物交互场景的几何与外观这一挑战性问题。基于动态3D高斯溅射方法，针对复杂交互中的相互遮挡与边缘模糊，提出交互感知的手物高斯，引入新可优化参数以采用分段线性假设，实现更清晰的结构表达。考虑到交互中手形与物体形状的互补性与紧密性，将手部信息融入物体形变场，构建交互感知的动态场以建模柔性运动。为应对优化困难，提出渐进式策略，分步处理动态区域与静态背景，并设计显式正则化，确保手物表示的平滑过渡、物理交互真实性及光照一致性。实验表明，该方法超越现有基于动态3D-GS的方法，在动态手物交互重建上达到当前最优性能。
原文摘要 · Abstract (English)
This paper focuses on a challenging setting of simultaneously modeling geometry and appearance of hand-object interaction scenes without any object priors. We follow the trend of dynamic 3D Gaussian Splatting based methods, and address several significant challenges. To model complex hand-object interaction with mutual occlusion and edge blur, we present interaction-aware hand-object Gaussians with newly introduced optimizable parameters aiming to adopt piecewise linear hypothesis for clearer structural representation. Moreover, considering the complementarity and tightness of hand shape and object shape during interaction dynamics, we incorporate hand information into object deformation field, constructing interaction-aware dynamic fields to model flexible motions. To further address difficulties in the optimization process, we propose a progressive strategy that handles dynamic regions and static background step by step. Correspondingly, explicit regularizations are designed to stabilize the hand-object representations for smooth motion transition, physical interaction reality, and coherent lighting. Experiments show that our approach surpasses existing dynamic 3D-GS-based methods and achieves state-of-the-art performance in reconstructing dynamic hand-object interaction.
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