Interfacial dynamics in two-phase flows govern momentum, heat, and mass transfer, yet remain difficult to measure experimentally. Classical techniques face intrinsic limitations near moving interfaces, while existing neural rendering methods target single-phase flows with diffuse boundaries and cannot handle sharp, deformable liquid-vapor interfaces. We propose SurfPhase, a novel model for reconstructing 3D interfacial dynamics from sparse camera views. Our approach integrates dynamic Gaussian surfels with a signed distance function formulation for geometric consistency, and leverages a video diffusion model to synthesize novel-view videos to refine reconstruction from sparse observations. We evaluate on a new dataset of high-speed pool boiling videos, demonstrating high-quality view synthesis and velocity estimation from only two camera views. Project website: https://yuegao.me/SurfPhase.
@article{arxiv.2602.11154,
title = {SurfPhase: 3D Interfacial Dynamics in Two-Phase Flows from Sparse Videos},
author = {Yue Gao and Hong-Xing Yu and Sanghyeon Chang and Qianxi Fu and Bo Zhu and Yoonjin Won and Juan Carlos Niebles and Jiajun Wu},
journal= {arXiv preprint arXiv:2602.11154},
year = {2026}
}
Comments
The first two authors contributed equally. Project website: https://yuegao.me/SurfPhase