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FiCA generates photorealistic avatars from a single image, achieving unprecedented visual quality and identity fidelity without the need for individual optimization.
Jointly modeling 3D geometry and relighting in a diffusion framework unlocks physically plausible single-image relighting that surpasses previous pipeline-based or geometry-agnostic approaches.
Training 3D avatar diffusion models on millions of in-the-wild videos is now possible, thanks to a clever 3D tokenization and visibility-aware training strategy that overcomes partial observability.
