AI RESEARCH
EgoFlow: Gradient-Guided Flow Matching for Egocentric 6DoF Object Motion Generation
arXiv CS.CV
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ArXi:2604.01421v1 Announce Type: new Understanding and predicting object motion from egocentric video is fundamental to embodied perception and interaction. However, generating physically consistent 6DoF trajectories remains challenging due to occlusions, fast motion, and the lack of explicit physical reasoning in existing generative models. We present EgoFlow, a flow-matching framework that synthesizes realistic and physically plausible trajectories conditioned on multimodal egocentric observations.