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To keep a character consistent in AI-generated video, anchor each shot to a clean reference image, reuse the model’s reference controls where available, and generate the story as short, clearly ordered scenes. For image-to-video, describe the movement and camera behavior rather than re-listing details already visible in the image. These steps reduce avoidable ambiguity, but no documented control guarantees a perfect identity match across every shot.
Why characters change between AI video shots
A video model has to interpret the subject, setting, style, and action from the inputs it receives. When separate shots are generated independently, small differences in those inputs or in the model’s interpretation can make a face, hairstyle, outfit, proportions, or other visual details shift. A long prompt alone is not a reliable substitute for a consistent visual anchor.
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For image-to-video, the source image already carries much of the subject’s appearance, composition, lighting, and style. Runway and Google both advise focusing the text prompt on what should move rather than repeating a full description of what is already in the image: Runway’s image-to-video guide and Google’s video best practices.
Build a continuity workflow before generating
1. Choose a clean character reference
Select or create one clear image that shows the details viewers need to recognize: face, hair, clothing, body shape, and any distinctive accessories. Start from a strong image; Runway warns that visual defects such as blurry faces or hands may become more pronounced in video. Google likewise describes the source image as the basis for character detail, lighting, and overall style.
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2. Plan the scenes in order
Write a shot list before generation. For each shot, note the character reference, setting, framing, intended action, and any deliberate changes to wardrobe or story state. This simple record helps distinguish an intentional change—such as a coat coming off—from unwanted drift. Treat it as a planning aid, not a model feature or a guarantee.
3. Reuse supported reference controls
When the tool supports reusable subject references, apply the same character reference across shots. Google’s Veo 3.1 documentation describes using up to three reference images to guide a person, character, or product. Runway describes Gen-4 references for maintaining consistency in subjects, styles, and locations. These are vendor-described capabilities, not proof of perfect identity lock: Google Veo 3.1 documentation and Runway Gen-4 overview.
4. Prompt for the action
For an image-to-video shot, say what the subject does, how the camera moves, and whether anything in the environment changes. For example: “The woman turns toward the window as the camera slowly pushes in; rain continues falling outside.” If the reference already establishes her appearance and the room, there is usually no need to restate every visual detail. Add a description only when you intend to change something.
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Keep each prompt focused on a simple action or sequence of actions. Runway recommends simple prompts for Gen-4 and says it generates 5- or 10-second clips. Its image-to-video guide recommends describing events sequentially and, when extending a longer sequence, using the completed generation’s last frame as the next input where supported. This gives the next shot a visual handoff, though it still does not guarantee a seamless continuation.
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6. Review and revise the actual output
Compare each result with the reference and adjacent shots. Check the face, hair, clothing, proportions, object placement, lighting, and location. If an identity detail changes, correct or replace the reference; if too many actions or changes are competing in one shot, split it into simpler shots and generate again. These checks are practical review steps, not a claim that a vendor has measured a specific continuity improvement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What Veo 3.1 and Runway Gen-4 document
| Tool | Documented continuity-relevant controls | Duration and constraints |
|---|---|---|
| Google Veo 3.1 | Up to three reference images can guide a person, character, or product. Documentation also describes first- and last-frame direction and video extension. A seed is available, but Google says it does not guarantee deterministic results, though it may slightly improve them. | Google documents 4-, 6-, or 8-second videos; reference-image use requires an 8-second video. Check the current model variant because settings and resolution constraints differ. |
| Runway Gen-4 | Generates video from an input image and text prompt; Runway’s guidance emphasizes high-quality inputs, simple positive phrasing, and motion-focused prompts. Its image-to-video guide also describes sequential prompting and continuing from a completed clip’s final frame. | Runway documents 5- or 10-second generations. Confirm current product settings and input constraints before starting. |
These are documented features and specifications, not a head-to-head test. Neither a reference image nor a seed should be treated as a promise that every frame or shot will preserve identity exactly. For a tool comparison, check the current version’s reference-image limits, frame or continuation controls, duration and resolution options, prompt controls, and availability in your location.
Is Sora available for this workflow?
No. OpenAI’s product page says Sora is no longer available as of April 26, 2026. Do not build a current workflow around it; check OpenAI’s Sora page for the product’s status.
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