HeteroPhys: Heterogeneous Physical Property Identification from Videos

Recovering physical properties from videos is essential for predicting object dynamics beyond observed interactions, yet direct identification of spatially heterogeneous physical fields remains underexplored. We present HeteroPhys, a framework for recovering heterogeneous physical parameter fields from multi-view videos of deformable objects. HeteroPhys extracts Lagrangian motion and local deformation histories and represents material properties in constitutive coordinates separating volumetric and deviatoric responses. A hierarchical conditional diffusion model reconstructs fields from coarse structure to fine spatial variation, while permutation-invariant fusion integrates evidence from multiple interactions. The predicted dense fields are further refined through differentiable MPM optimization. We construct a benchmark with ground-truth heterogeneous fields across elastic and plasticine materials. Experiments show that HeteroPhys generalizes to unseen geometries, benefits from additional interaction evidence, and remains predictive under unseen interaction conditions.