← 研踪 PaperTrailarXiv:2611.07979 · v1
Perception Over Geometry: Rethinking Gaussian Allocation in Mesh-based Splatting
首次提交 2026-11-05 21:09
版本更新 2026-11-05 21:09
雷达观测 2026-11-06 11:06
摘要
3D Gaussian Splatting (3DGS) enables photorealistic novel-view synthesis but lacks explicit topology for geometric editing. Existing mesh-based methods enable geometric manipulation by associating Gaussians with triangular mesh faces, typically assigning a fixed number of Gaussians to each face. However, the representation capacity required for appearance reconstruction depends on local appearance complexity rather than merely on mesh tessellation density. To address these limitations, we propose P-MGS, a framework that separates appearance modeling from geometric control to achieve high quality rendering, compact representation, and flexible mesh editing. P-MGS introduces a perceptual complexity guided allocation strategy that distributes Gaussians according to surface appearance demand estimated from multiview observations. To preserve reconstruction flexibility, Gaussians are optimized without mesh constraints and subsequently associated with the original mesh through post hoc binding, retaining adaptive refinement while preserving mesh topology. During mesh editing, local affine deformation transfer updates Gaussian centers and covariances under mesh deformation, reducing misalignment and floating artifacts. Experiments demonstrate superior average novel view synthesis quality with fewer Gaussians and coherent mesh editing.
作者备注:10 pages, 7 figures
观测到的版本
相邻记录可能跳过中间版本;首次发现 v2 及以上也会标为版本更新。
v1 · 2026-11-05 21:09 · 最新观测版本
Perception Over Geometry: Rethinking Gaussian Allocation in Mesh-based Splatting
3D Gaussian Splatting (3DGS) enables photorealistic novel-view synthesis but lacks explicit topology for geometric editing. Existing mesh-based methods enable geometric manipulation by associating Gaussians with triangular mesh faces, typically assigning a fixed number of Gaussians to each face. However, the representation capacity required for appearance reconstruction depends on local appearance complexity rather than merely on mesh tessellation density. To address these limitations, we propose P-MGS, a framework that separates appearance modeling from geometric control to achieve high quality rendering, compact representation, and flexible mesh editing. P-MGS introduces a perceptual complexity guided allocation strategy that distributes Gaussians according to surface appearance demand estimated from multiview observations. To preserve reconstruction flexibility, Gaussians are optimized without mesh constraints and subsequently associated with the original mesh through post hoc binding, retaining adaptive refinement while preserving mesh topology. During mesh editing, local affine deformation transfer updates Gaussian centers and covariances under mesh deformation, reducing misalignment and floating artifacts. Experiments demonstrate superior average novel view synthesis quality with fewer Gaussians and coherent mesh editing.
查看此版本解读 →查看此版本原文 ↗