ArtMesh：带有运动一致动态的部件感知可变形网格场
ArtMesh: Part-Aware Articulated Mesh Fields with Motion-Consistent Dynamics
AI总结：
ArtMesh通过构建基于网格的可微渲染基础，实现了从多视角图像中重建可变形物体的连接三角网格，并在100个新基准数据集上超越了现有3DGS方法。
摘要：
我们提出了ArtMesh，一种基于网格的方法，用于从起始和结束状态的多视角图像中显式重建可变形物体，作为具有每部分刚性运动的连接三角网格。现有基于3D高斯点散射的可变形重建管道继承了其点散射基础的无结构点几何，无法提供表面拓扑来推断部件边界或沿物体连接性的运动一致性。ArtMesh相反，建立在基于网格的可微渲染基础之上，使部件感知动态能够直接作用于结构拓扑。为了使拓扑与可变形兼容，我们引入了部件感知受限德劳内重新三角化，产生连接的子网格，其三角形不跨越语义部件边界。动态网格场然后通过双向顶点运动一致性优化可变形性，通过传输网格顶点和像素级运动一致性优化渲染的RGB-D观察。我们引入了Articulate-100，一个包含100个可变形物体的16个PartNet-Mobility类别的新基准。在该基准上，ArtMesh在关节参数估计和部件级几何重建上优于现有3DGS方法，其在具有许多可动部件的物体上收益最大。
英文摘要：
We present ArtMesh, a mesh-native method for reconstructing articulated objects explicitly as connected triangle meshes with per-part rigid motion from multi-view images in start and end states. Existing 3D Gaussian Splatting pipelines for articulated reconstruction inherit the unstructured point-based geometry of their splatting base, which provides no surface topology for reasoning about part boundaries or enforcing motion consistency along the object's connectivity. ArtMesh instead builds on a mesh-based differentiable rendering backbone, enabling part-aware dynamics to act directly on the structured topology. To make the topology compatible with articulation, we introduce part-aware restricted Delaunay remeshing, producing connected submeshes whose triangles do not cross semantic part boundaries. The dynamic mesh field then optimizes articulation using bidirectional Vertex-wise Motion Consistency on transported mesh vertices and Pixel-wise Motion Consistency on rendered RGB-D observations. We introduce Articulate-100, a new benchmark of 100 articulated objects spanning 16 PartNet-Mobility categories. On this benchmark, ArtMesh outperforms prior 3DGS-based pipelines in joint parameter estimation and part-level geometric reconstruction, with the largest gains on objects with many movable parts.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
