AI RESEARCH
FG-Portrait: 3D Flow Guided Editable Portrait Animation
arXiv CS.CV
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ArXi:2603.23381v1 Announce Type: new Motion transfer from the driving to the source portrait remains a key challenge in the portrait animation. Current diffusion-based approaches condition only on the driving motion, which fails to capture source-to-driving correspondences and consequently yields suboptimal motion transfer. Although flow estimation provides an alternative, predicting dense correspondences from 2D input is ill-posed and often yields inaccurate animation. We address this problem by.