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This paper introduces KnockGS, a novel framework that calibrates the elasticity and density of 3D Gaussian representations by leveraging the interaction response of deformable objects under known applied forces. By extracting temporal response features from observed dynamics, the framework enables accurate estimation of material parameters that can be integrated back into the simulation, enhancing the fidelity of the object's physical behavior. The results demonstrate that KnockGS significantly outperforms existing methods in parameter recovery and response-level accuracy across various material targets, showcasing its potential for interactive physical simulations.
Interaction response can be harnessed to accurately calibrate material properties of 3D Gaussian representations, outperforming traditional methods by a substantial margin.
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.
