AI video continuity

Keeping a generated cut consistent

On a film set someone sits with a notebook so the jacket is on the same shoulder tomorrow. Generated video has no notebook and no set. Every shot is made on its own, so the jacket, the room and the weather are all up for renegotiation each time.

This is what actually goes wrong, and the working order that keeps a long cut from falling apart.

Drop a video here, or click to pick one

MP4 · MOV · WEBM · up to 5 GB

What breaks, in order of how often

None of these are exotic. They are the same mistakes a script supervisor writes down on a live set, just arriving faster and in bulk.

The person
A face settles slightly differently every time it is generated. Hair length, a beard, the shape of a jaw.
The clothes
A jacket comes off between two shots that are meant to be the same minute. A shirt changes shade.
The things they hold
A glass moves hands. A record is on the table in one shot and on the shelf in the next.
The room
Furniture shifts, a window appears on the other wall, the light turns from afternoon into evening.
Where they stand
Two people swap sides of the frame, so a conversation suddenly turns the wrong way.
The weather and the clock
Rain in one shot, dry ground in the next. Long shadows, then no shadows at all.

There is a longer walk through the categories on continuity errors, and the face and wardrobe side has its own page on character consistency.

Always compare to the first shot

This is the one habit that changes the most. Pick the shot where a person or a place is clearest, treat it as the truth, and measure everything later against it. Comparing each shot to the one before hides drift, because every step looks close enough to the step behind it.

ReferenceShot 01Shot 02Shot 03Shot 04Shot 05
One reference. Every later shot held up against it, not against its neighbour.

A working order

  1. 01

    Pick your reference shot

    Whichever shot shows the person or the room most clearly. Everything later gets held up against it, not against the shot before it.

  2. 02

    Generate against the reference, not the last frame

    Chaining each shot off the previous one is how drift compounds. Small changes stack until shot twelve has nothing to do with shot one.

  3. 03

    Cut first, check second

    Continuity only matters in the order the audience sees it. Assemble the sequence, then look for breaks across the cut.

  4. 04

    Decide what is deliberate

    If she takes the coat off on camera, it is not an error. Keep a short list of changes the story explains, and ignore flags that match it.

  5. 05

    Regenerate the shot, not the sequence

    Fix the one shot that broke, keep the rest, and re-check. Redoing everything just gives you a fresh set of problems.

Where the check saves you time

Doing this by eye means scrubbing a five minute cut over and over, holding shot one in your head while you watch shot twenty. That is the part worth handing off. Upload the cut and you get a score, a timeline with a mark wherever something stops matching, the two frames that disagree, and a written fix for each mark.

Shots0102030405Break
Every mark on the timeline opens the two frames that disagree.
Established0:09Contradicts0:41Fix
Each problem comes with the change to make, in plain text you can copy.

If you want the measurement itself, how the clip is read and how the number is worked out, that is on AI video analysis. Published runs sit on the benchmark.

What it cannot do for you

It does not know your story. If the coat is meant to come off, it can flag that as a break, and you are the one who decides it is fine. It also works from a compressed copy of your clip, so something wrong for half a second can slip past. Treat it as a second pair of eyes near the end of the edit, not as a sign-off.