ArtMesh: Part-Aware Articulated Mesh Fields with Motion-Consistent Dynamics

TL;DR

ArtMesh is a novel mesh-based method for reconstructing articulated objects with explicit part-aware topology and motion consistency, improving over point-based approaches.

Contribution

We introduce ArtMesh, a mesh-native articulated reconstruction method with part-aware topology and a new benchmark for evaluation.

Findings

Outperforms prior 3D Gaussian Splatting pipelines in joint estimation.

Achieves better part-level geometric reconstruction.

Largest improvements on objects with many movable parts.

Abstract

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.