FreeArtGS：自由移动场景下的关节高斯泼溅
FreeArtGS: Articulated Gaussian Splatting Under Free-moving Scenario
FreeArtGS 提出了一种从自由移动的单目 RGB-D 视频中重建关节物体的新设定，利用现成的点跟踪和特征模型先验进行部件分割与关节估计，并基于 3DGS 端到端优化视觉纹理、几何与关节角度。对视觉研究者而言，其可复用的技术点包括：利用相对运动进行无监督刚性部件分割、从分割结果鲁棒恢复关节类型与轴、以及将 3DGS 扩展到关节物体的联合优化框架。
原文依据 FreeArtGS combines free-moving part segmentation with joint estimation and end-to-end optimization, taking only a monocular RGB-D video as input.
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论增强现实和机器人技术日益增长的需求推动了对高可扩展性关节物体重建的需要。然而，现有的从离散关节状态或随意单目视频中重建的设置需要非平凡的轴对齐或面临覆盖不足的问题，限制了其适用性。本文介绍了 FreeArtGS，一种在自由移动场景下重建关节物体的新方法，该场景是一种设置简单且可扩展性高的新设定。FreeArtGS 将自由移动部件分割与关节估计和端到端优化相结合，仅以单目 RGB-D 视频作为输入。通过利用现成的点跟踪和特征模型的先验进行优化，自由移动部件分割模块在无约束捕获下从相对运动中识别刚性部件。关节估计模块校准统一的物体到相机姿态，并从部件分割中稳健地恢复关节类型和轴。最后，实现基于 3DGS 的端到端优化，以联合重建关节物体的视觉纹理、几何和关节角度。我们在两个基准和真实世界的自由移动关节物体上进行了实验。实验结果表明，FreeArtGS 在重建自由移动关节物体方面始终表现出色，并且在先前的重建设置中保持高度竞争力，证明其是现实资产生成的实用且有效的解决方案。项目页面见：https://freeartgs.github.io/。
英文原文摘要 1582 字符
The increasing demand for augmented reality and robotics is driving the need for articulated object reconstruction with high scalability. However, existing settings for reconstructing from discrete articulation states or casual monocular videos require non-trivial axis alignment or suffer from insufficient coverage, limiting their applicability. In this paper, we introduce FreeArtGS, a novel method for reconstructing articulated objects under free-moving scenario, a new setting with a simple setup and high scalability. FreeArtGS combines free-moving part segmentation with joint estimation and end-to-end optimization, taking only a monocular RGB-D video as input. By optimizing with the priors from off-the-shelf point-tracking and feature models, the free-moving part segmentation module identifies rigid parts from relative motion under unconstrained capture. The joint estimation module calibrates the unified object-to-camera poses and recovers joint type and axis robustly from part segmentation. Finally, 3DGS-based end-to-end optimization is implemented to jointly reconstruct visual textures, geometry, and joint angles of the articulated object. We conduct experiments on two benchmarks and real-world free-moving articulated objects. Experimental results demonstrate that FreeArtGS consistently excels in reconstructing free-moving articulated objects and remains highly competitive in previous reconstruction settings, proving itself a practical and effective solution for realistic asset generation. The project page is available at: https://freeartgs.github.io/.