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WARPED: Wrist-Aligned Rendering for Robot Policy Learning from Egocentric Human Demonstrations
Recent advancements in learning from human demonstration have shown promising results in addressing the scalability and high cost of data collection required to train robust visuomotor policies. However, existing approaches are often constrained by a reliance on multiview camera setups, depth sensor
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