What Is Identity Preservation in AI Video?
Identity preservation refers to an AI video model's ability to keep a specific person's actual face, features, and likeness intact throughout a generated clip — rather than drifting toward a generic or different-looking face as the motion plays out.
Why it's a real technical challenge
Generating multiple consistent frames of motion is harder than generating one still image — small inconsistencies between frames can accumulate into a face that subtly drifts away from the original photo by the end of the clip if the model isn't specifically built to guard against it.
How prompts help enforce it
Explicit instructions — preserve the same face, facial features, skin tone, hairstyle, expression — are built directly into the generation prompt precisely to keep the model anchored to the original photo's identity throughout every frame.
Why it matters for trust
An effect that keeps someone clearly recognizable feels like a fun transformation of a real photo; one that drifts into a different-looking face starts to feel more like a face-swap, which is a very different (and less desired) kind of result for this format.
Is identity preservation the same as face-swapping?
The opposite, actually — face-swapping replaces one person's face with another's, while identity preservation is specifically about keeping the original person's own face intact throughout an effect.
