StructuredField: Unifying Structured Geometry and Radiance Field
Kaiwen Song, Jinkai Cui, Zherui Qiu, Juyong Zhang

TL;DR
StructuredField introduces a novel structured tetrahedral mesh representation for high-fidelity, differentiable rendering that integrates well with existing graphics pipelines and simulation algorithms, ensuring geometric integrity and multi-scale detail capture.
Contribution
The paper presents a new structured mesh-based representation with a conformal, inversion-free tetrahedral mesh and a reparameterization into 3D Gaussian primitives for differentiable rendering.
Findings
Achieves high-quality, inversion-free, conformal tetrahedral meshes.
Provides comparable reconstruction quality to existing methods like 3DGS.
Demonstrates applicability to physical simulation, deformation, and level-of-detail tasks.
Abstract
Recent point-based differentiable rendering techniques have achieved significant success in high-fidelity reconstruction and fast rendering. However, due to the unstructured nature of point-based representations, they are difficult to apply to modern graphics pipelines designed for structured meshes, as well as to a variety of simulation and editing algorithms that work well with structured mesh representations. To this end, we propose StructuredField, a novel representation that achieves both a structured geometric representation of the reconstructed object and high-fidelity rendering reconstruction. We employ structured tetrahedral meshes to represent the reconstructed object. We reparameterize the geometric attributes of these tetrahedra into the parameters of 3D Gaussian primitives, thereby enabling differentiable, high-fidelity rendering directly from the mesh. Furthermore, a…
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Taxonomy
TopicsComputer Graphics and Visualization Techniques · Computational Geometry and Mesh Generation
