arXiv Computer Vision

Elastic Triangle Splatting

arXiv Computer Vision
Sep 30

MeshSplatBench: A Unified Benchmark for Triangle- and Mesh-Based Neural Rendering

MeshSplatBench is the first benchmark designed to evaluate triangle- and mesh-based neural rendering methods from native rendering to deployment in graphics engines such as Unity and Blender. It introduces a hierarchical deployment protocol with standard and dedicated options, and a structural audit for mesh splatting to assess topological and geometric integrity. The benchmark’s evaluations show that graphics engine deployment degrades quality, dedicated deployment preserves fidelity at a significant speed cost, and current mesh splatting methods lack sufficient connectivity for manifoldness.

By Kaixuan Zhang, Minxian Li, Mingwu Ren, Xiatian Zhu
arXiv Computer Vision
Sep 25

ToCo-Mesh: Topology-Consistent Dynamic Mesh Reconstruction via Adaptive Tessellation and Surface-Aligned 2DGS

ToCo-Mesh is a dynamic mesh reconstruction framework that preserves topology consistency while achieving high‑fidelity geometry from multi‑view temporal images. It uses a dual‑mesh representation, coupling a canonical template mesh to time‑varying coarse guide meshes via barycentric parameterization, and applies error‑driven split‑and‑merge operations on the template to refine detail. A Surface‑Aligned 2DGS module anchors flattened Gaussians to mesh faces, using rendered normals to guide fine‑tuning and suppress surface irregularities, resulting in photorealistic rendering.

By Chuanjin Fan, Wenjie Chang, Aibing Li, Bingzhou Wang, Wenfei Yang, Tianzhu Zhang
arXiv Machine Learning
Aug 5

Robust Biharmonic Skinning Using Geometric Fields

arXiv:2406. 00238v3 Announce Type: replace-cross Abstract: Bounded bihramonic weights are a popular tool used to rig and deform characters for animation, to compute reduced-order simulations, and to define feature descriptors for geometry processing.

By Ana Dodik, Vincent Sitzmann, Justin Solomon, Oded Stein
arXiv Computer Vision
Aug 25

Differentiable Voxelization of Surface Representations

The paper introduces a differentiable voxelization technique that computes gradients of volumetric properties, such as winding numbers, with respect to surface mesh parameters. This method allows efficient optimization of triangle meshes using voxel-based volume samples on a regular grid. The authors demonstrate its utility in applications like resolving mesh intersections, designing manufacturable shapes for bandsaw cutting, and creating near-tiling 3D structures.

By Tobias Djuren, Ugo Finnendahl, Markus Worchel, Hendrik Meyer, Marc Alexa
arXiv AI
Sep 4

TruncGradGS: Improved 3D Gaussian Splatting via Truncated Gradient Updates

The paper introduces TruncGradGS, a piecewise truncated gradient approach that mitigates gradient vanishing in 3D Gaussian Splatting, enhancing optimization stability and robustness to initializations. It demonstrates consistent improvements over random and COLMAP initializations in both static and dynamic settings. Additionally, the authors highlight limitations of existing dynamic scene benchmarks and present a new synthetic dataset for evaluating dynamic Gaussian Splatting.

By Theo Morales, Nhat-Quynh Le-Pham, Robin Atkins, Binh-Son Hua
arXiv Computer Vision
Sep 18

RGS: Reflection-aware Gaussian Splatting via Learning Geometry Continuity for Reflective Objects

The paper introduces Reflection-aware Gaussian Splatting (RGS), a physically-based deferred rendering framework that improves novel view synthesis for reflective objects. RGS leverages a powerful 3D foundation model to provide a strong geometric prior and employs cross-view shape consistency regularization to prevent surface collapse and reduce geometric hollows. Additionally, a reflection-aware densification strategy captures specular variations across views, resulting in higher-quality renderings of reflective objects.

By Xiaobiao Du, Yida Wang, Cheng Bi, Kun Zhan, Xin Yu
arXiv Machine Learning
Jul 28

Meshless Domain Randomization via Explicit Parameter Perturbation of 3D Gaussian Splatting

arXiv:2607. 22890v1 Announce Type: cross Abstract: Domain Randomization (DR) is a standard technique for closing the Sim-to-Real gap, yet traditional DR pipelines rely on classical computer graphics rendering driven by polygon meshes.

By Felipe Nunes Carbone de Carvalho, Joyce de Morais Souza, Alan de Aguiar, Charles Morphy D. Santos, Jo\~ao Paulo Gois