Article

DepState-JEPA: Depth-Grounded State Representation Learning for Visual Perception and Manipulation

The authors propose DepState-JEPA, a dual-stream RGB-D joint-embedding predictive architecture that connects spatial understanding with action-conditioned prediction through a shared latent state, DepState. Built on V-JEPA 2.1, the framework uses depth both as a complementary observation stream and as the grounding for metric 3D space, and constrains state learning with ray-conditioned readouts, object-trajectory supervision, and calibrated forward kinematics.

Part of the event: DepState-JEPA Dual-Stream RGB-Depth State Representation Research Released

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