How to Keep Characters Consistent in AI Video

A recurring presenter, mascot or customer character only works if viewers recognise them in every shot. This playbook sets out a workflow for holding one character steady across a multi-shot AI video, and how Runway, Kling AI, Google Flow, Higgsfield and Adobe Firefly handle references, caps and permissions.

This applies to multi-shot video with a recurring person, mascot or product, made in tools that accept image or video references. References reduce drift, but no tool documents identical results, so keep review and regeneration in the budget.

Why Do AI Video Characters Change Between Shots?

AI video characters change between shots because every generation rebuilds the character from its inputs, and Runway's Gen-4 References guide warns that adding more variables increases variation, so results may differ even from the same reference. A changed word, a new light source or a fast head turn gives the model room to redraw the face, outfit and proportions.

Even with saved references, AI video generation tools rebuild the character on every clip rather than carrying an actor from one shot to the next. Each prompt, reference image and first frame is a fresh instruction, and the model fills every gap with a new guess. Text alone leaves the most gaps, which is why the same description can return a different jawline or jacket in the next shot.

If you are new to the format, start with what AI video generation is and how its text, image and video inputs differ.

Set that as the team's goal. A viewer should never wonder whether the presenter in shot four is the presenter from shot one. References, fixed prompts and frame chaining reduce drift, and a continuity review with targeted regeneration catches what still slips through.

How To Build A Character Reference Set

A character reference set is a front-facing main image plus one to three extra angles, shot in even light with a neutral expression on a plain background, because Kling's Element Library guide asks for 2 to 4 images led by a front-facing one and Google Flow's help centre recommends plain or segmented backgrounds.

Build the set once, approve it, and treat it as the character's master record. Every later shot, test and fix goes back to it.

What goes into the set:

• Main image. Front-facing with a neutral expression, the "blank canvas" Runway's References tips ask for.
• Extra angles. One to three more views, such as three-quarter and profile, matching Kling's 1 to 3 supplementary angles.
• Even light. Natural, even lighting and moderate image quality, as Runway advises.
• Plain background. A plain or segmented backdrop, so the model reads the subject rather than the room.
• One look. The same hair, outfit and accessories in every image, since Google Flow asks for a consistent look across ingredient images.
• Outfit variants. Each change of clothes approved as a separate still, so it becomes a reference in its own right.
• Voice clip (optional). One speaker only. Kling binds a voice from a 5 to 30 second clip, and Google Flow accepts a single-speaker voice reference with ingredients.

What each tool asks for:

• Runway Gen-4 References uses up to three active references per generation.
• Kling AI elements take 2 to 4 images, led by a front-facing main image.
• Google Flow ingredients work best on a plain or segmented background.
• Higgsfield Soul ID trains on 20 or more well-lit photos at different angles.

One Runway tip helps with location and style images. If such a photo already contains a face, Runway suggests covering that face with a black box before uploading, so it does not compete with your character.

• Main image is front-facing with a neutral expression
• One to three extra angles match the main image
• Lighting is natural and even in every image
• Backgrounds are plain or segmented
• Hair, outfit and accessories match across the set
• Each outfit variant is a separate approved still
• Any voice clip has one speaker only
• Written permission is on file for any real person
• The set is saved and named in each tool you use

Which AI Video Tools Support Character References?

Runway, Kling AI, Google Flow, Higgsfield and Adobe Firefly all accept character references, but they store them differently, from Runway's tagged Gen-4 References and Kling's Element Library to Higgsfield's trained Soul ID, while Adobe's own reusable-character feature, Elements, is still in private beta. That difference decides how a character persists between sessions.

Read the table as a map of where the character lives. In Runway and Kling AI it sits in a saved library you call by name. In Higgsfield it is a trained identity. In Google Flow the same ingredient images carry it from clip to clip, and in Adobe Firefly it travels through first frames and the partner model's own references.

All five are AI video generation tools, so the workflow in this playbook applies to each of them. If you are still choosing one, compare AI video generators for marketing teams first.

Runway Gen-4 References Then Image To Video

Runway keeps a character consistent in two steps, a Gen-4 References still built from up to three tagged references and then that still used as the first frame of a video whose prompt describes only the motion.

Reference method: Upload the reference images, then tag each one with a name (hover over it, click the tag icon, type a name and press Enter). In the prompt, type @ to call a saved reference by name.

Reference limit: Up to three active references per generation, enough for a character, a location and a product in one prompt.

Persistence: Uploads stay temporary until they are tagged with a name. Tag the approved set before the first shot.

Video handoff: Click the camera icon on an approved still to load it into the latest video model. Gen-4 Video uses the input image as the first frame, makes 5 or 10 second clips and wants a prompt "almost entirely focused on describing the desired motion". A fixed seed gives generations with similar motion, which helps when you retake one shot.

Permissions and access: Treat consent as a team control in Runway. Keep the signed release for any real person alongside the tagged reference, and let one owner tag and retire the references for a brand character.

Limitation: Runway's Gen-4 Video help article is marked as covering an older model generation and points to Gen-4.5 for text-to-video and image-to-video, so confirm which model your handoff lands in before you lock a seed and a shot list.

Running cost: Gen-4 uses 12 credits per second of video and Gen-4 Turbo uses 5, so a 5-second Gen-4 clip costs 60 credits. Test motion on Turbo and render the keeper on Gen-4.

Teams weighing Runway against presenter-led avatar tools can read Runway vs HeyGen for the wider comparison.

Kling AI Elements And The Element Library

Kling AI stores a recurring character as an element in its Element Library, built from 2 to 4 reference images or a 3 to 8 second clip, and a VIDEO 3.0 Omni generation can call up to seven elements by name with the @ symbol.

Reference method: Build a multi-image element from at least 2 images, one main and one additional, up to 4 in total. Kling recommends a front-facing main image with 1 to 3 supplementary angles. In VIDEO 3.0 Omni, a character element can instead come from a 3 to 8 second clip of one character, uploaded or recorded in the app, with a voice bound from a 5 to 30 second single-person clip, the Voice Library or "No Voice".

Reference limit: VIDEO 3.0 Omni and O1 take up to 7 elements when the input has no video and up to 4 when it does. VIDEO 3.0 start and end frames take up to 3 additional bound elements, which should appear in the reference frames.

Persistence: Elements stay in the Element Library under a cap set by membership. Non-members can store 30 elements, Standard members 50, Pro and Premier members 150, and Ultra members 500.

Video handoff: There is no separate step. In Omni, type @ to call an element by its name, which must be unique within the library.

Permissions and access: The character library is tied to the plan. After a downgrade, existing elements stay usable, but you cannot create or edit elements above the new cap, so a team with a large cast should budget for the tier that holds it.

Limitation: Elements cannot be shared to Kling's Explore feed, though videos made with them can be. The reference set, not the element, is what you hand to a colleague or agency.

Running cost: Creating an element is free. AI multi-view completion gives members 3 free uses a day and then costs 5 credits a use, and non-members pay 5 credits a use.

Google Flow Ingredients, Frames And Avatars

Google Flow keeps a character consistent through Ingredients to Video, where the same reference images are reused across clips, and Google's Veo 3.1 model behind it accepts up to three reference images of a character, object or scene.

Reference method: Drag reference images or video into Flow as ingredients. Put subject references on a plain or segmented background, keep their look consistent, and write a prompt that will "complement, not contradict, your visual inputs".

Reference limit: Veo 3.1 accepts up to 3 reference images of a character, object or scene for consistency across shots.

Persistence: Reuse the same ingredient images for every clip of a character. Your own likeness can also live as an avatar, called with @me in the prompt, carrying your visual and audio likeness.

Video handoff: Frames to Video takes a start frame, an end frame or both, and the prompt describes the action or transition between them. Veo 3.1 scene extension builds each new clip from the final second of the previous one, for videos of a minute or more.

Permissions and access: Avatars feature your own likeness only, go through recitation and safety checks, cannot be shared via Google Flow Tools or public project links, and are not available in the EEA, the UK or Switzerland. A single-speaker voice reference works only with ingredients, and other generations return an error.

Limitation: Google says feature availability may differ by country or region of use and that certain image types may not be supported, so confirm each team member's access before you build a shared workflow.

Running cost: Each generation draws on Flow credits, so the cost of consistency sits in retakes. Fixed ingredients and frame chaining cut the attempts a shot needs.

Higgsfield Soul ID Character Training

Higgsfield's Soul ID trains a reusable character identity from 20 or more well-lit photos and applies it to both image and video generation, including video models such as Veo 3.1 and Kling 3.0.

Reference method: Upload well-lit photos of one person at different angles and train a Soul ID. Higgsfield says training takes 3 to 5 minutes on Soul 2.0.

Reference limit: Higgsfield's spec table recommends 20 or more photos and accepts up to 80.

Persistence: The trained identity is reusable across image and video generation inside Higgsfield.

Video handoff: Higgsfield says the identity carries into video models such as Seedance 2.0, Veo 3.1 and Kling 3.0, with Cinema Studio for camera control.

Permissions and access: Higgsfield allows training on someone else's photos only if you hold usage rights to them. Keep that proof on file before you train an identity for a colleague, actor or customer.

Limitation: Higgsfield's own guide gives two different photo counts in different places, so prepare the larger set from its spec table. The identity also lives in Higgsfield, not in the downstream video model, so it does not follow the character into a project run directly in Kling AI or Google Flow.

Adobe Firefly Partner Models And Reference Frames

Adobe Firefly keeps a video character consistent through first frames and partner models such as Kling 3.0, which supports reusable elements inside Firefly, while Adobe's own Elements feature for saved characters remains in private beta.

Reference method: Choose a partner model that takes references. Gemini Omni Flash accepts up to four reference images, and Kling 3.0 supports reusable elements built from reference images.

Reference limit: Up to four reference images in Gemini Omni Flash. Kling 3.0 and 3.0 Omni make videos of up to 15 seconds with up to five shots.

Persistence: Adobe has announced Firefly Elements, an upcoming feature for defining characters, locations and objects and reusing them across images and video. It is in private beta, so build today's workflow on saved reference files and Kling 3.0 elements.

Video handoff: A first frame is mandatory for Kling in Firefly. Ray models take a first frame and an optional last frame, and Runway Gen-4.5 takes a start image.

Permissions and access: Selecting a partner model prompts you to confirm you are using a model not developed by Adobe, which matters if your brand policy approves Adobe models only.

Limitation: Firefly's own reusable-character feature is not generally available, so consistency depends on partner models and the files you bring to each shot.

Running cost: Firefly plans count video in generative credits and five-second videos. Standard includes 2,000 credits a month and up to 20 five-second videos, Pro 4,000 credits and up to 40, Pro Plus 10,000 credits and up to 100, and Premium 50,000 credits with unlimited Firefly Video Model access.

How To Write Scene Constraints For AI Video

Scene constraints fix everything about a shot except the one thing you mean to change, and when a reference image already carries the character, Runway's Gen-4 guide says the prompt should focus almost entirely on the desired motion.

Split every prompt into four blocks and treat three of them as locked:

• Identity block. The character, written once and copied word for word into every prompt, or replaced by the saved reference tag (an @ name in Runway or Kling AI, @me for a Google Flow avatar).
• Scene block. Location, lighting and wardrobe state. It changes only when the story moves to a new place or outfit.
• Motion block. Action and camera. This is the only block that changes from shot to shot.
• Exclusions line. What must not appear, such as extra people, a new hairstyle or changed logos.

With an image input, describe motion, not appearance. Runway's Gen-4 Video guide asks for a prompt "almost entirely focused on describing the desired motion", because the image already carries the look. Google Flow's help centre says the prompt should complement, not contradict, the visual inputs. A prompt that re-describes the face invites the model to redraw it.

Rule: Change one variable per shot. If shot three changes the camera, keep the action and light from shot two. Runway's References tips say more variables increase variation, so every extra change is another chance for the face to slip.

IDENTITY (locked, copy unchanged or use the saved tag)
@{{character-name}}, {{age-range}}, {{hair-colour-and-style}}, {{eye-colour}}, {{build}}, wearing {{approved-outfit-name}}

SCENE (locked until location or wardrobe changes)
{{location}}, {{time-of-day}}, {{light-source-and-direction}}, {{colour-temperature}}

A three-shot presenter sequence shows the pattern:

1. Shot one. The presenter speaks to camera in a static medium shot.
2. Shot two. Same framing and light, and the presenter turns to the screen. Only the action changes.
3. Shot three. The presenter holds the turn while the camera pushes in slowly. Only the camera changes.

With an image or first frame attached, shorten the identity block to the tag and let the reference carry the look. Without one, the identity block is the only anchor, so it must stay word for word identical in every shot.

For the full anatomy of a prompt, including camera language and audio, read how to write prompts for AI video.

How To Keep Characters Consistent Across Multiple Shots

To carry a character across shots, start each new clip from an approved frame of the last one, because Google's Veo 3.1 scene extension builds every new clip from the final second of the previous clip to hold visual continuity.

1. Write a shot list. Note the location, wardrobe, action and camera for each shot, and mark where location or wardrobe changes.
2. Test the hardest shot first. Head turns and wide shots are where faces and proportions slip, so generate a short test of them before anything else. Runway's Gen-4 Video makes 5 or 10 second clips, and the shorter one is the cheaper test.
3. Approve a frame. Pick the frame where the character best matches the reference set and save it.
4. Chain the next shot from it. Use it as the first frame in Runway, as a start frame in Google Flow's Frames to Video or Kling AI's VIDEO 3.0, or extend the scene in Veo 3.1 from the last second.
5. Fix the seed where offered. Runway's fixed seed gives generations with similar motion, which keeps a retake close to its neighbours.
6. Repeat the references in every shot. Attach the same reference set or saved element each time rather than chaining only from outputs, so small drifts do not build up shot after shot.

Decision rule: Chain from frames when the next shot continues the action in the same place. Restart from the reference set when the location or wardrobe changes, because a chained frame carries the old setting with it.

Long sequences need the same care at every join. Veo 3.1 scene extension reaches a minute or more, and Kling 3.0 in Firefly makes up to five shots in one video of up to 15 seconds, but each join is still a point where the character can change.

How To Review Continuity In AI Video

A continuity review compares every shot with the approved reference set on face, hair, outfit, proportions and light, and fixes one difference at a time, which Runway's References guide recommends for complex changes.

Run it twice, once per shot as it is generated and once per cut when shots sit side by side in the edit. Drift that passes in a single clip often shows at a cut.

• Face matches the main reference image (eyes, nose, jaw, skin tone)
• Hair length, colour and parting match
• Outfit, accessories and logos match the approved still
• Proportions hold in wide shots and at full body
• Lighting direction and colour temperature match the scene block
• Voice matches the bound or reference voice, where used
• Hands, props and products keep their shape between cuts
• No extra or duplicated character appears

Fixing drift: Regenerate only the failing shot and change one variable at a time. Runway's guide advises editing one element at a time and using each result as a new reference, so when a regenerated frame improves on the set, approve it into the set.

Team rules: Name one continuity owner who signs off each shot. Agree the pass bar in advance, for example that a viewer must not question the character's identity at any cut. Log every approved frame with its tool, model, seed and reference names, so a retake weeks later starts from the same inputs.

How Much Does Character Consistency Cost In AI Video Credits?

Character consistency costs credits mainly through retakes, and Runway's help centre puts its Gen-4 model at 12 credits per second of video against 5 for Turbo, so testing shots on the cheaper model before the final render cuts the bill. Every test shot, retake and extension draws on the same allowance.

Three things drive the spend:

• Retakes. Each regeneration of a drifting shot uses the same credits as the first attempt.
• Clip length. Runway charges per second, so a 5-second Gen-4 clip uses 60 credits and a 10-second one uses 120.
• Stored-reference features. Creating a Kling AI element is free, while AI multi-view completion costs 5 credits a use after a member's 3 free daily uses.

Runway's plans set the monthly ceiling. Standard includes 625 credits a month, Pro 2,250 with top-ups at any time, and Max 9,500 with unused credits rolling over for one month. The minimum top-up purchase is 1,000 credits. At Gen-4's rate, the Standard allowance covers about 52 seconds of video, retakes included.

Adobe Firefly counts video in five-second videos per plan, from up to 20 on Standard to up to 100 on Pro Plus. A sequence that needs four takes per shot uses four of them for each final shot.

Plan prices for Runway and Adobe Firefly:

Decision rule: Test motion and framing on the cheaper or faster model, then render approved shots on the higher one. In Runway that means Gen-4 Turbo before Gen-4, and Firefly lists Veo 3.1 Fast alongside Veo 3.1 among its partner models.

What Permissions Do You Need For A Real Person's Likeness In AI Video?

Using a real person as a recurring AI video character needs that person's permission and, in the EU, a label, since Article 50 of the AI Act requires deployers to disclose that deepfakes are artificially generated from 2 August 2026. Get written consent before the person's photos or voice enter any reference set.

Consent first: Permission sits with you, not the tool. Higgsfield allows training a Soul ID on someone else's photos only if you hold usage rights. Google Flow avatars cover your own visual and audio likeness only and are not available in the EEA, the UK or Switzerland. For a colleague, actor or customer, get a written release that covers their face and voice, the tools you will use and where the video will run.

EU disclosure: Article 50(4) makes deployers disclose AI-generated or manipulated deepfakes. For evidently artistic, creative, satirical or fictional work, the duty is limited to disclosing in a way that does not hamper the display or enjoyment of the work.

What counts as a deepfake: Secure Privacy, a compliance firm, reads the European Commission's Article 50 guidelines broadly. In its summary, content that closely resembles a real person and could mislead a reasonable viewer is covered even without a sophisticated impersonation, and satirical or fictional work gets a reduced, not a full, exemption.

YouTube: YouTube requires creators to disclose realistic altered or synthetic content that a viewer could mistake for a real person, place, scene or event, including a face swap or a synthetically generated voice. Clearly unrealistic or animated content, special effects, colour and lighting adjustments and beauty filters do not need disclosure.

For a recurring brand character, the rules split two ways. A realistic presenter based on a real employee needs a release, and a disclosure label on YouTube and under the EU rules. A clearly animated mascot that resembles no real person falls outside YouTube's disclosure rule. For presenter-led video, our comparison of AI avatar video tools and consent goes further into custom avatars.

This section is general information, not legal advice.

Frequently Asked Questions

Text prompts alone rarely hold a character steady, because each generation reinterprets the words, so Runway, Kling AI and Google Flow all ask for reference images to carry the character's look.