AI RESEARCH
ExpPortrait: Expressive Portrait Generation via Personalized Representation
arXiv CS.CV
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ArXi:2602.19900v2 Announce Type: replace While diffusion models have shown great potential in portrait generation, generating expressive, coherent, and controllable cinematic portrait videos remains a significant challenge. Existing intermediate signals for portrait generation, such as 2D landmarks and parametric models, have limited disentanglement capabilities and cannot express personalized details due to their sparse or low-rank representation.