The team collected 216 human bimanual trajectories involving 26 objects, totaling 61,684 time-aligned multimodal data frames. Based on the MAE architecture, VTAO-BiManip recovers complete environmental interactions from partial observations through cross-modal fusion, achieving a success rate over 20% higher than existing methods in both simulation and real-world environments. The research has been published at IROS.