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i-PhysGaussian: Implicit Physical Simulation for 3D Gaussian Splatting

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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.

Yicheng Cao, Zhuo Huang, Yu Yao, Yiming Ying, Daoyi Dong, Tongliang Liu• 2026

Related benchmarks

TaskDatasetResultRank
Over-exposure DiagnosticAlocasia
SAT Mean (%)15
4
Over-exposure DiagnosticHAT
SAT Mean5
4
Physical SimulationPhysGaussian Ficus synthetic
kmax20
4
Physical SimulationPhysGaussian Pillow2Sofa synthetic
Kmax20
4
Physical SimulationPhysGaussian Bread synthetic
kmax20
4
Physical Simulation Drift EvaluationFicus
COMD AUC0.0184
4
Physical Simulation Drift EvaluationBread
COMD AUC0.0138
4
Physical Simulation Drift EvaluationPillow2Sofa
COMD AUC0.0023
4
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