Key Features

Restylizes source videos while preserving facial identity and performance.
Uses edited keyframes to guide scene style, lighting, and background changes.
Supports relighting as a constrained version of the broader restylization task.
Handles imperfect keyframes by re-aligning motion after the first frame.
Uses facial normal maps and relit facial regions as preservation controls.
Supports single-subject and multi-subject video examples.
Provides project materials with paper, code link, and demo videos.
Targets production-quality video editing and visual storytelling research.

The method decouples edit-driven synthesis from source-grounded identity preservation. It uses relit facial regions, facial normal maps, edited keyframes, and depth sequences so the model can propagate a new style or lighting setup while re-aligning to the original performance after imperfect keyframes.


ID-V2V is useful for filmmakers, VFX teams, and researchers exploring controllable video-to-video generation. It supports restylization and relighting workflows where the creative look can change substantially without sacrificing the actor's facial motion and identity.

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