Quadratic Gaussian Splatting: High Quality Surface Reconstruction with Second-Order Geometric Primitives
Ziyu Zhang, Binbin Huang, Hanqing Jiang, Liyang Zhou, Xiaojun Xiang, Shuhan Shen
Abstract
We propose Quadratic Gaussian Splatting (QGS), a novel representation that replaces static primitives with deformable quadric surfaces (e.g., ellipse, paraboloids) to capture intricate geometry. Unlike prior works that rely on Euclidean distance for primitive density modeling-a metric misaligned with surface geometry under deformation-QGS introduces geodesic distance-based density distributions. This innovation ensures that density weights adapt intrinsically to the primitive curvature, preserving consistency during shape changes (e.g., from planar disks to curved paraboloids). By solving geodesic distances in closed form on quadric surfaces, QGS enables surfaceaware splatting, where a single primitive can represent complex curvature that previously required dozens of planar surfels, potentially reducing memory usage while maintaining efficient rendering via fast ray-quadric intersection. Experiments on DTU, Tanks and Temples, and MipNeRF360 datasets demonstrate state-of-the-art surface reconstruction, with QGS reducing geometric error (chamfer distance) by 33% over 2 DGS and 27% over GOF on the DTU dataset. Crucially, QGS retains competitive appearance quality, bridging the gap between geometric precision and visual fidelity for applications like robotics and immersive reality.
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Cited by top-tier papers8
- Radiance Meshes for Volumetric ReconstructionAlexander Mai, Trevor Hedstrom, George Kopanas, Janne Kontkanen et al.CVPR 2026 · 8 citations
- PlanarGS: High-Fidelity Indoor 3D Gaussian Splatting Guided by Vision-Language Planar PriorsXirui Jin, Renbiao Jin, Boying Li, Danping Zou et al.NeurIPS 2025 · 5 citations
- Universal Beta SplattingRong Liu, Zhongpai Gao, Benjamin Planche, Meida Chen et al.ICLR 2026 · 4 citations
- ExMesh: EXplicit Mesh Reconstruction with Topology AdaptationChuanjin Fan, Lifan Wu, Wenjie Chang, Hanzhi Chang et al.CVPR 2026 · 2 citations
- 3D Gaussian Splatting with Self-Constrained Priors for High Fidelity Surface ReconstructionTakeshi Noda, Yu-Shen Liu, Zhizhong HanCVPR 2026 · 2 citations
Builds on27
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 5,687 citations
- Instant neural graphics primitives with a multiresolution hash encodingThomas Müller, Alex Evans, Christoph Schied, Alexander KellerSIGGRAPH 2022 · 4,089 citations
- Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance FieldsJonathan T. Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman et al.ICCV 2021 · 2,700 citations
- NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view ReconstructionPeng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt et al.NeurIPS 2021 · 2,500 citations
- Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance FieldsJonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan et al.CVPR 2022 · 1,603 citations
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