无需模板即可自动重建可重定姿态的动态物体3D模型
Template-free Articulated Gaussian Splatting for Real-time Reposable Dynamic View Synthesis
- 用3D高斯点云与超点重构动态物体，通过刚性部分推断骨骼结构
- 实现高分辨率图像实时渲染，视觉保真度优异
- 适合需要快速生成可动3D模型的应用场景
尽管动态场景的新视角合成已取得显著进展，但捕捉物体的骨架模型并进行重定姿态仍具挑战。本文提出一种新方法，无需对象特定模板即可从视频中自动发现动态物体的骨骼模型。该方法结合3D高斯点云与超点技术重建动态物体，将超点视为刚性部件，通过直观线索推断底层骨骼结构，并利用运动学模型优化。此外，采用自适应控制策略避免冗余超点产生。大量实验表明，本方法在获得可重定姿态3D物体方面高效且有效，不仅能实现出色的视觉保真度，还支持高分辨率图像的实时渲染。
原文摘要 · Abstract (English)
While novel view synthesis for dynamic scenes has made significant progress, capturing skeleton models of objects and re-posing them remains a challenging task. To tackle this problem, in this paper, we propose a novel approach to automatically discover the associated skeleton model for dynamic objects from videos without the need for object-specific templates. Our approach utilizes 3D Gaussian Splatting and superpoints to reconstruct dynamic objects. Treating superpoints as rigid parts, we can discover the underlying skeleton model through intuitive cues and optimize it using the kinematic model. Besides, an adaptive control strategy is applied to avoid the emergence of redundant superpoints. Extensive experiments demonstrate the effectiveness and efficiency of our method in obtaining re-posable 3D objects. Not only can our approach achieve excellent visual fidelity, but it also allows for the real-time rendering of high-resolution images.
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