Controllable Egocentric Video Generation via Occlusion-Aware Sparse 3D Hand Joints

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• The method exhibits exceptional cross-embodiment generalization to robotic hands.result 90%
• The proposed framework generates egocentric videos from a single reference frame using sparse 3D hand joints as embodiment-agnostic control signals.method 95%
• The method introduces an efficient control module that resolves occlusion ambiguities while fully preserving 3D information.technical 90%
• The control module extracts occlusion-aware features by penalizing unreliable visual signals from hidden joints.technical 85%
• The approach significantly outperforms state-of-the-art baselines in generating high-fidelity egocentric videos.result 85%
• Existing methods struggle with 3D-consistent fine-grained hand articulation and often collapse 3D geometry into spatially ambiguous signals.limitation 80%
• An automated annotation pipeline was developed that yields over one million high-quality egocentric video clips paired with precise hand trajectories.method 90%
• The method's 3D-based weighting mechanism robustly handles dynamically occluded target joints during motion propagation.technical 80%

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