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WARPED: Synthesizing wrist-view observations from first-person human demonstrations to train robot visuomotor policies

WARPED is a framework that synthesizes realistic wrist-view observations and actions from human demonstration videos, enabling visuomotor policy training with only monocular RGB data. The system uses vision foundation models to initialize the interactive scene, employs a hand-object interaction pipeline to track the hand and manipulated object and retarget trajectories to a robotic end-effector, and finally uses Gaussian Splatting to synthesize photorealistic wrist-view observations for directly training policies.

Part of the event: WARPED Synthesizes Wrist-View Training for Robot Policies from Monocular Human Demonstrations

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