GaussianFluent: Gaussian Simulation for Dynamic Scenes with Mixed Materials

Bei Huang, Yixin Chen, Ruijie Lu, Gang Zeng, Hongbin Zha +2 more
1/14/2026
cs.CV

No confident code implementation found for this paper.

Abstract

3D Gaussian Splatting (3DGS) has emerged as a prominent 3D representation for high-fidelity and real-time rendering. Prior work has coupled physics simulation with Gaussians, but predominantly targets soft, deformable materials, leaving brittle fracture largely unresolved. This stems from two key obstacles: the lack of volumetric interiors with coherent textures in GS representation, and the absence of fracture-aware simulation methods for Gaussians. To address these challenges, we introduce GaussianFluent, a unified framework for realistic simulation and rendering of dynamic object states. First, it synthesizes photorealistic interiors by densifying internal Gaussians guided by generative models. Second, it integrates an optimized Continuum Damage Material Point Method (CD-MPM) to enable brittle fracture simulation at remarkably high speed. Our approach handles complex scenarios including mixed-material objects and multi-stage fracture propagation, achieving results infeasible with previous methods. Experiments clearly demonstrate GaussianFluent's capability for photo-realistic, real-time rendering with structurally consistent interiors, highlighting its potential for downstream application, such as VR and Robotics.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{huang2026gaussianfluent,
  title  = {GaussianFluent: Gaussian Simulation for Dynamic Scenes with Mixed Materials},
  author = {Bei Huang and Yixin Chen and Ruijie Lu and Gang Zeng and Hongbin Zha and Yuru Pei and Siyuan Huang},
  year   = {2026},
  eprint = {2601.09265},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2601.09265v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2601.09265.svg)](https://codeofpaper.com/paper/2601.09265)

Discussion