AI character consistency: diagnose the drift, then fix it

Cause 1: missing angles

Symptom: the face is right when the character faces the camera and wrong in profile, from above, or as they turn. The ear or the back of the head changes from clip to clip.

Why: the model can only copy what it was shown. Every angle missing from the references is generated fresh each time, and fresh guesses differ.

Fix: add the missing view. A profile and a three-quarter view solve most cases. If your model accepts video, a few seconds of the person turning their head covers angles that stills miss. Kling's guide for Kling 3.0 Omni, for example, lets you build a character element from a 3 to 8 second clip.

Cause 2: conflicting signals

Symptom: the character looks like a blend. Hair between two colors, a jacket that is half one style and half another, an age that seems to shift.

Why: two inputs disagree and the model averages them. The usual culprits are a prompt that describes the character differently from the images, or references taken months apart with different hair.

Fix: make every input agree. Remove character description from the prompt and keep only scene, action and camera. Drop any reference that does not match the others. If you want a new look, build a new reference set rather than asking the prompt to override the old one.

Cause 3: identity bleeding between characters

Symptom: in a two-person shot, features move between characters. He gets her eye color, she gets his beard shadow, or both drift toward an average face.

Why: the model holds two identities at once and does not know which features belong to whom.

Fix: give each character its own named element or tagged image set, and refer to each by its tag in every sentence, never as he or she. Keep the characters apart at the start of the shot. Avoid two lookalikes in one frame; contrast makes separation easier.

Cause 4: small faces and fast motion

Symptom: identity holds in close-ups but falls apart in wide shots, action scenes or anything with motion blur.

Why: when a face is only a few dozen pixels tall, there is no room to render identity. Fast motion makes it worse, because the model rebuilds the face from blurred frames.

Fix: cut to a medium shot before identity matters, use a higher resolution for shots where the face is small, and slow the action down in the prompt. If a wide shot must stay wide, accept that it carries less identity and let the next close-up do the work.

Cause 5: style and light overriding references

Symptom: the character is correct in neutral scenes and changes in stylized ones, such as anime, claymation, film noir, strong neon or firelight.

Why: style and strong colored light change skin tone, hair color and facial structure, and a heavy style prompt can outweigh the references.

Fix: if the series has a style, make the references in that style. Keep extreme lighting to shots where the face is not the focus. Test one stylized scene before committing a whole batch.

Cause 6: length and randomness

Symptom: the character starts right and slowly changes over a long clip, or one clip in a batch is off while others with the same inputs are fine.

Why: identity errors build up over long clips, and every generation has a random component.

Fix: prefer several shorter shots joined by cuts over one long take, even on models that allow 15 or 30 seconds. For one-off misses, regenerate with identical inputs. If the same miss repeats, it is not random and belongs to one of the causes above.

Making the fixes stick

Once a reference set produces the right character, freeze it, along with the model and format. Most fixes above are changes to inputs, and a workflow that lets inputs wander brings the drift back. In RefVid, a character is saved once as an asset with 1 to 5 images, and every clip runs on Kling 3.0 Omni from exactly that set. All of the character's clips sit on one page, so drift shows up quickly.