KnockGS:interaction-Grounded Calibrationof Physical Gaussian Representations
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Abstract (arXiv)
Physics-integrated 3D Gaussian representations now allow reconstructed deformable objects to be simulated and rendered under explicit material models. Existing pipelines, however, assume that material parameters are known or manually specified, limiting their applicability when these parameters must be inferred from observed object dynamics. We propose KnockGS, an interaction-response PhysicalGS framework that estimates the elasticity and density scales of a 3D Gaussian object from its dynamics under a known applied force. Rather than treating physical simulation only as a forward process, we turn the force-induced response into a calibration signal: temporal response features are xtracted from the observed dynamics, the two material scales are estimated from those features, and the estimate is then frozen and written back into the same simulator so that it can be tested on an interaction it was never fitted to.We evaluate the framework on both parameter recovery and response-level fidelity. The estimated scales are compared against hidden ground truth, and the re-simulated object is measured against the target using 3D particle trajectories, response-curve statistics, and rendered-frame quality. Across five held-out material targets, our method recovers the scales substantially more accurately than response retrieval, global regression, or a fixed default material, and the frozen estimate remains predictive under interactions that differ in direction and in magnitude. Interaction response therefore carries enough information to calibrate material scales in physically grounded 3D Gaussian representations.Our study is a first step toward interactive PhysicalGS systems that calibrate a Gaussian asset whose rendered appearance and simulated response are consistent.
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References · 25
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
- 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,032
- 2023Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesiscited by 737
- 2023PhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamicscited by 377
- 2023PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identificationcited by 154
- 2024ManiGaussian: Dynamic Gaussian Splatting for Multi-task Robotic Manipulationcited by 108
- 2024Reconstruction and Simulation of Elastic Objects with Spring-Mass 3D Gaussianscited by 97
- 2025PhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videoscited by 87
- 2024SplatSim: Zero-Shot Sim2Real Transfer of RGB Manipulation Policies Using Gaussian Splattingcited by 69
- 2025OmniPhysGS: 3D Constitutive Gaussians for General Physics-Based Dynamics Generationcited by 69
- 2024AdaptiGraph: Material-Adaptive Graph-Based Neural Dynamics for Robotic Manipulationcited by 54
13 more
- 2024GIC: Gaussian-Informed Continuum for Physical Property Identification and Simulationcited by 49
- 2024Efficient Physics Simulation for 3D Scenes via MLLM-Guided Gaussian Splattingcited by 32
- 2025PUGS: Zero-shot Physical Understanding with Gaussian Splattingcited by 24
- 2024GaussianProperty: Integrating Physical Properties to 3D Gaussians with LMMscited by 23
- 2025PhysGM: Large Physical Gaussian Model for Feed-Forward 4D Synthesiscited by 10
- 2025PhysGS: Bayesian-Inferred Gaussian Splatting for Physical Property Estimationcited by 7
- 2026GaussianFluent: Gaussian Simulation for Dynamic Scenes with Mixed Materialscited by 7
- 2026Learning Physics-Grounded 4D Dynamics with Neural Gaussian Force Fieldscited by 6
- 2026ReconPhys: Reconstruct Appearance and Physical Attributes from Single Videocited by 5
- 2025ProJo4D: Progressive Joint Optimization for Sparse-View Inverse Physics Estimationcited by 4
- 2026FastPhysGS: Accelerating Physics-based Dynamic 3DGS Simulation via Interior Completion and Adaptive Optimizationcited by 4
- 2026i-PhysGaussian: Implicit Physical Simulation for 3D Gaussian Splattingcited by 3
- 2026DiffWind: Physics-Informed Differentiable Modeling of Wind-Driven Object Dynamicscited by 3
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