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arXiv 提交日期: 2026-02-19
📄 Abstract - i-PhysGaussian: Implicit Physical Simulation for 3D Gaussian Splatting

Physical simulation predicts future states of objects based on material properties and external loads, enabling blueprints for both Industry and Engineering to conduct risk management. Current 3D reconstruction-based simulators typically rely on explicit, step-wise updates, which are sensitive to step time and suffer from rapid accuracy degradation under complicated scenarios, such as high-stiffness materials or quasi-static movement. To address this, we introduce i-PhysGaussian, a framework that couples 3D Gaussian Splatting (3DGS) with an implicit Material Point Method (MPM) integrator. Unlike explicit methods, our solution obtains an end-of-step state by minimizing a momentum-balance residual through implicit Newton-type optimization with a GMRES solver. This formulation significantly reduces time-step sensitivity and ensures physical consistency. Our results demonstrate that i-PhysGaussian maintains stability at up to 20x larger time steps than explicit baselines, preserving structural coherence and smooth motion even in complex dynamic transitions.

顶级标签: computer vision systems model training
详细标签: 3d gaussian splatting physical simulation implicit integration material point method 3d reconstruction 或 搜索:

i-PhysGaussian:用于3D高斯泼溅的隐式物理模拟框架 / i-PhysGaussian: Implicit Physical Simulation for 3D Gaussian Splatting


1️⃣ 一句话总结

这篇论文提出了一个名为i-PhysGaussian的新框架,它将先进的3D场景重建技术与一种更稳定、更高效的物理模拟方法相结合,使得在模拟复杂物体运动(如坚硬材料或缓慢移动)时,可以使用比传统方法大20倍的时间步长,而不会损失精度或导致模拟崩溃。

源自 arXiv: 2602.17117