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MeGAS: Thermomechanical Dynamic Gaussian Splatting for Thermophysical Scene Editing,
Zesong Yang*, Yuanhang Lei*, Liyuan Cui, Yihang Chen, Jiaer Huang, Boming Zhao, Peter Yichen Chen, Hujun Bao, Zhaopeng Cui†
Abstract: Recent advances integrate physically grounded Newtonian dynamics with neural rendering frameworks, narrowing the gap between photorealistic scene reconstruction and physics-based animation. However, existing approaches focus on mechanically driven dynamics while neglecting temperature, a fundamental yet invisible physical factor underlying phenomena such as melting, solidification, and other thermomechanical processes. In this paper, we propose MeGAS, a novel framework that incorporates thermomechanical phase-change dynamics into 3D Gaussian Splatting (3DGS). Specifically, we propose a new thermomechanical dynamic Gaussian Splatting representation that augments 3DGS with temperature attributes and employs a heat advection-diffusion solver with MPM dynamics incorporating phase transitions, enabling physically plausible and visually realistic synthesis of thermophysical phenomena. Furthermore, a new topology-adaptive Gaussian rendering strategy is proposed to mitigate cracking and floaters under extreme deformation. Extensive experiments demonstrate that MeGAS produces physically consistent thermomechanical behavior while maintaining high-fidelity photorealistic rendering, advancing toward physics-integrated world models.
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Some codes are modified from PhysGaussian, Warp-MPM, thanks for the authors for their valuable works.
If you find this code useful for your research, please use the following BibTeX entry.
@inproceedings{yang2025megas,
title={MeGAS : Thermomechanical Dynamic Gaussian Splatting for Thermophysical Scene Editing},
author={Yang, Zesong and Lei, Yuanhang and Cui, Liyuan and Chen, Yihang and Huang, Jiaer and Zhao, Boming and Chen, Peter Yichen and Bao, Hujun and Cui, Zhaopeng},
booktitle={European Conference on Computer Vision (ECCV)},
year={2026}
}