YOCO: You Only Calibrate Once! Fast Mocap Calibration for Dexterous Teleoperation
YOCO introduces a fast calibration framework that corrects biases in low-cost hand-pose streams using few-shot learning. It conditions a network on paired raw and target poses to predict LoRA updates for a frozen hand estimation module. This method improves downstream dexterous teleoperation performance significantly, achieving high success rates by inferring session-specific noise from minimal calibration data.