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NeuROK Learns Data-Driven 4D Object Kinematics Without Predefined Physics Models
May 27, 2026
NeuROK learns a latent kinematic state space for 4D object deformation without assuming a predefined physical model, avoiding the category-specific limitations of system identification approaches. The method targets realistic temporal deformations under varied physical conditions for use in 3D world models.
paper
HOW THIS AFFECTS YOU
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researcherThe data-driven kinematic parameterization sidesteps the need for physics priors, which could generalize better across object categories than existing 4D synthesis methods.