# GaMeS: Mesh-Based Adapting and Modification of Gaussian Splatting

arXiv: https://arxiv.org/abs/2402.01459 · HTML: https://mlsanity.com/paper/2402.01459/

## Key facts

- Cited by 70 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 44 references that are in the map.
- First posted on arXiv 2 Feb 2024.

## Builds on (most cited first, 19 of 19)

- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://mlsanity.com/paper/2201.05989/) (2022)
- [Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields](https://mlsanity.com/paper/2111.12077/) (2021)
- [Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields](https://mlsanity.com/paper/2103.13415/) (2021)
- [Plenoxels: Radiance Fields without Neural Networks](https://mlsanity.com/paper/2112.05131/) (2021)
- [Efficient Geometry-aware 3D Generative Adversarial Networks](https://mlsanity.com/paper/2112.07945/) (2021)
- [4D Gaussian Splatting for Real-Time Dynamic Scene Rendering](https://mlsanity.com/paper/2310.08528/) (2023)
- [SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering](https://mlsanity.com/paper/2311.12775/) (2023)
- [Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes](https://mlsanity.com/paper/2101.10994/) (2021)
- [SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes](https://mlsanity.com/paper/2312.14937/) (2023)
- [GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussians](https://mlsanity.com/paper/2312.02069/) (2023)
- [VR-GS: A Physical Dynamics-Aware Interactive Gaussian Splatting System in Virtual Reality](https://mlsanity.com/paper/2401.16663/) (2024)
- [Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision](https://mlsanity.com/paper/1905.06817/) (2019)
- [NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)](https://mlsanity.com/paper/2210.00379/) (2022)
- [EfficientNeRF: Efficient Neural Radiance Fields](https://mlsanity.com/paper/2206.00878/) (2022)
- [NeRFMeshing: Distilling Neural Radiance Fields into Geometrically-Accurate 3D Meshes](https://mlsanity.com/paper/2303.09431/) (2023)
- [NeuralEditor: Editing Neural Radiance Fields via Manipulating Point Clouds](https://mlsanity.com/paper/2305.03049/) (2023)
- [Flexible Techniques for Differentiable Rendering with 3D Gaussians](https://mlsanity.com/paper/2308.14737/) (2023)
- [NeRFlame: FLAME-based conditioning of NeRF for 3D face rendering](https://mlsanity.com/paper/2303.06226/) (2023)

## Built on by (most cited first, 30 of 70)

- [Recent Advances in 3D Gaussian Splatting](https://mlsanity.com/paper/2403.11134/) (2024)
- [GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Views](https://mlsanity.com/paper/2404.01810/) (2024)
- [4D LangSplat: 4D Language Gaussian Splatting via Multimodal Large Language Models](https://mlsanity.com/paper/2503.10437/) (2025)
- [HAHA: Highly Articulated Gaussian Human Avatars with Textured Mesh Prior](https://mlsanity.com/paper/2404.01053/) (2024)
- [GauStudio: A Modular Framework for 3D Gaussian Splatting and Beyond](https://mlsanity.com/paper/2403.19632/) (2024)
- [GASP: Gaussian Splatting for Physic-Based Simulations](https://mlsanity.com/paper/2409.05819/) (2024)
- [Mani-GS: Gaussian Splatting Manipulation with Triangular Mesh](https://mlsanity.com/paper/2405.17811/) (2024)
- [GeoSplatting: Towards Geometry Guided Gaussian Splatting for Physically-based Inverse Rendering](https://mlsanity.com/paper/2410.24204/) (2024)
- [Beyond Gaussians: Fast and High-Fidelity 3D Splatting with Linear Kernels](https://mlsanity.com/paper/2411.12440/) (2024)
- [Quadratic Gaussian Splatting: High Quality Surface Reconstruction with Second-order Geometric Primitives](https://mlsanity.com/paper/2411.16392/) (2024)
- [StreetSurfGS: Scalable Urban Street Surface Reconstruction with Planar-based Gaussian Splatting](https://mlsanity.com/paper/2410.04354/) (2024)
- [MeshGS: Adaptive Mesh-Aligned Gaussian Splatting for High-Quality Rendering](https://mlsanity.com/paper/2410.08941/) (2024)
- [D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup](https://mlsanity.com/paper/2405.14276/) (2024)
- [iHuman: Instant Animatable Digital Humans From Monocular Videos](https://mlsanity.com/paper/2407.11174/) (2024)
- [DreamWaltz-G: Expressive 3D Gaussian Avatars from Skeleton-Guided 2D Diffusion](https://mlsanity.com/paper/2409.17145/) (2024)
- [MiraGe: Editable 2D Images using Gaussian Splatting](https://mlsanity.com/paper/2410.01521/) (2024)
- [Grounding Creativity in Physics: A Brief Survey of Physical Priors in AIGC](https://mlsanity.com/paper/2502.07007/) (2025)
- [Direct and Adaptable Mesh-Gaussian Scene Reconstruction from Multi-View Images](https://mlsanity.com/paper/2405.06945/) (2024)
- [MaGS: Reconstructing and Simulating Dynamic 3D Objects with Mesh-adsorbed Gaussian Splatting](https://mlsanity.com/paper/2406.01593/) (2024)
- [VeGaS: Video Gaussian Splatting](https://mlsanity.com/paper/2411.11024/) (2024)
- [PICA: Physics-Integrated Clothed Avatar](https://mlsanity.com/paper/2407.05324/) (2024)
- [Self-supervised Learning of Hybrid Part-aware 3D Representations of 2D Gaussians and Superquadrics](https://mlsanity.com/paper/2408.10789/) (2024)
- [Cloth-Splatting: 3D Cloth State Estimation from RGB Supervision](https://mlsanity.com/paper/2501.01715/) (2025)
- [Radiance Meshes for Volumetric Reconstruction](https://mlsanity.com/paper/2512.04076/) (2025)
- [SA-GS: Semantic-Aware Gaussian Splatting for Large Scene Reconstruction with Geometry Constrain](https://mlsanity.com/paper/2405.16923/) (2024)
- [Hypo3D: Exploring Hypothetical Reasoning in 3D](https://mlsanity.com/paper/2502.00954/) (2025)
- [PR-ENDO: Physically Based Relightable Gaussian Splatting for Endoscopy](https://mlsanity.com/paper/2411.12510/) (2024)
- [GeoTexDensifier: Geometry-Texture-Aware Densification for High-Quality Photorealistic 3D Gaussian Splatting](https://mlsanity.com/paper/2412.16809/) (2024)
- [Decomposing Densification in Gaussian Splatting for Faster 3D Scene Reconstruction](https://mlsanity.com/paper/2507.20239/) (2025)
- [AG2aussian: Anchor-Graph Structured Gaussian Splatting for Instance-Level 3D Scene Understanding and Editing](https://mlsanity.com/paper/2508.01740/) (2025)

## Abstract (arXiv)

Gaussian Splatting (GS) is a novel, state-of-the-art technique for rendering points in a 3D scene by approximating their contribution to image pixels through Gaussian distributions, warranting fast training and real-time rendering. The main drawback of GS is the absence of a well-defined approach for its conditioning due to the necessity of conditioning several hundred thousand Gaussian components. To solve this, we introduce the Gaussian Mesh Splatting (GaMeS) model, which allows modification of Gaussian components in a similar way as meshes. We parameterize each Gaussian component by the vertices of the mesh face. Furthermore, our model needs mesh initialization on input or estimated mesh during training. We also define Gaussian splats solely based on their location on the mesh, allowing for automatic adjustments in position, scale, and rotation during animation. As a result, we obtain a real-time rendering of editable GS.