Troubleshooting
How to approach face drift in an AI duo video
Find where the likeness changes and make a focused adjustment before another attempt.
Written and maintained by A2O LITE NEON AI · Updated
Locate the change first
Face drift describes a likeness that changes during the clip. It can become more noticeable in profile, during turns, fast movement or occlusion. Watch the full output and note the time and affected subject. A single thumbnail can conceal the issue or exaggerate a brief change that needs to be assessed in motion.
Inspect the reference information
If the face is tiny, hidden by hair or heavily smoothed, try a clearer unobstructed photo. Verify the upload role and keep one subject in each reference. Adding aggressive sharpening or filters can introduce artificial texture. When a better original is available, use it instead of repeatedly processing the problematic image.
Change one main variable
If one subject loses likeness, try replacing that subject’s photo while keeping the other reference and roles unchanged. Record the time of the problem and compare the full clips. Each new generation uses another attempt; a different photo may help but cannot guarantee exact identity or movement.
Separate quality concerns from failure
A completed clip with an imperfect likeness is not automatically a failed task. video attempts are returned for confirmed failed generations; a temporary network error alone does not establish failure. When contacting support, include the task ID, the time of the issue and a brief description. Do not send passwords or payment credentials.