According to Fei-Fei Li (@drfeifei), Dream2Flow introduces a robot policy representation based on 3D object-centered flow to generalize manipulation from generated videos to real-world control, improving open-world robustness; as reported by Wenlong Huang (@wenlong_huang), the method bridges video generation and robot control by extracting object-level spatial motion cues, enabling better transfer across scenes and viewpoints, and the project site (dream2flow.github.io) details how object flow serves as an intermediate representation for policy learning with potential for scalable data synthesis and lower sim-to-real costs.