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Workflows • Updated • 7 min read

Two-Character AI Scenes: References, Masks and Review

Plan two-character AI scenes with separate references, composition notes and a review worksheet. Compare masking and compositing without identity guarantees.

Apatero reference, generation and review workflow illustration

Correction, September 20, 2026: Earlier versions reported unsupported consistency percentages and described LoRA trigger words as spatial switches. They are not. This replacement explains the boundaries of regional conditioning and offers a proposed scene-planning procedure, without claiming a completed comparison.

For two-character AI scenes, define each character separately, decide their placement and choose a generation path that accepts the inputs you need. A supported multi-reference model, a compatible masked-conditioning workflow and separate generation followed by compositing are different options. None guarantees two unchanged faces or correct physical interaction.

Start with a scene you can judge. Two fictional characters sitting on opposite sides of a cafe table are easier to describe in a review sheet than an undefined request for “a cinematic duo.”

Choose The Path Before Writing The Prompt

Path What You Prepare What You Must Check
Supported Multi-Reference Generation Separate reference images and a scene brief Whether the model accepts those inputs and assigns each character correctly
Masked Conditioning In A Compatible Workflow References, masks, compatible models and documented nodes Whether text and image conditioning both reach the intended regions
Separate Generation And Compositing Individual character images and a shared composition plan Scale, perspective, light, shadows and believable contact

This is a planning comparison, not a performance ranking. Choose based on the controls you can actually use and the interaction the scene requires. A composite can offer direct placement control, but a handshake may require substantial work where the bodies meet.

Make A Casting Sheet

Give each fictional character a neutral identifier, such as A and B. Attach the approved image and list the details that matter to this scene. A might wear a blue sweater and glasses; B might have short dark hair and a brown jacket. These are illustrative descriptions, not evidence of generated results.

Then assign positions: A on the left looking right, B on the right looking left, both seated at the same table. Record which hand holds a cup, which body parts are hidden and whether the characters touch. These decisions become review criteria.

Keep shared details in a separate scene brief: cafe interior, window on the left, table between the characters. A common description of lighting is useful direction, but it cannot ensure that both rendered faces receive physically consistent illumination.

Regional Text Is Not The Same As A Regional LoRA

ComfyUI includes conditioning nodes that attach area or mask information to text conditioning. Its ordinary LoRA loader instead applies patches to the model and text encoder. Placing a trigger word in a regional prompt does not, by itself, restrict those patches to that part of the image. These are distinct operations in the ComfyUI core implementation.

If a tutorial promises regional LoRAs, inspect the exact extension and graph that implement the restriction. Do not infer it from where an activation word appears. A downloadable graph should identify its models, nodes and versions; without that information, a prose recipe is not a reproducible setup.

Image conditioning needs a separate check. Two IPAdapter instances do not automatically mean that each reference is isolated to one character. A compatible masking configuration must connect each reference to the intended influence area, and the resulting image still needs inspection.

The cubiq IPAdapter documentation provides model-specific requirements and examples. Its FaceID companion LoRAs should not be confused with separately trained character LoRAs. The repository is in maintenance-only mode, so check compatibility with your installation before relying on an older workflow.

Our IPAdapter evaluation worksheet shows how to record settings without inventing a universal best weight. Start from the documentation for your exact configuration, then change one variable at a time.

Plan Masks Around The Actual Composition

For the cafe example, draw rough regions over a composition sketch. A straight left/right split may suit two equally sized seated figures. It becomes less useful when one person leans across the table or stands behind the other.

Check the masks against the intended body positions. Record their boundaries and any overlap. Do not assume a mask that covers a face also covers that person's jacket, hands or moving arm. The shared table can make this assignment awkward; that is a reason to inspect the output closely, not proof that an overlap automatically resolves the scene.

Pose conditioning is another optional input when the selected workflow supports it. It can communicate the intended arrangement, but a pose reference is not evidence that the output has correct fingers, contact or identity. Verify permissions for any photographs used as inputs.

Use A Small, Recorded Comparison

The following is a proposed procedure. It has not been run for this article.

  1. Save the approved references for A and B and the cafe composition sketch.
  2. Record the exact model, node versions and available reference settings.
  3. Generate the planned scene through the selected path, preserving every output.
  4. Review identity assignment, clothing, gaze, body contact and scene geometry.
  5. Identify one failure before changing a setting or mask.
  6. Save the revision alongside the original and state whether it solved that failure.

Use a worksheet with these columns:

Record Purpose
Attempt ID And Output Keep accepted and rejected images traceable
A/B References Show which source represents each character
Prompts And Masks Preserve spatial assignments and shared scene instructions
Model And Optional Adapters Make the configuration inspectable
Identity And Clothing Catch swaps and blended distinguishing features
Interaction Check gaze, hands, contact and body placement
Environment Check perspective, table shape, lighting and shadows
Decision And Cost Record the rejection reason and actual charge

Do not turn a few pleasing outputs into an accuracy percentage. A comparison needs a defined acceptance rule and retained failures before a rate has meaning.

When Compositing Is The More Controllable Edit

You can generate the characters separately, extract them with an editing tool and place them into a shared scene. Do not assume the generation output already has usable transparency. Check edges around hair and glasses, then align scale and perspective before judging the faces.

Work through the contact areas next. A cup should rest on the table, a hand should grip it and a chair should support the seated person. A further edit or inpainting pass may help, but it can also alter an already approved face. Compare the edited region and the rest of the image with the previous version.

For sequential storytelling, keep these records with the comic page plan, so a successful scene does not become an untraceable one-off image.

Where Saved Characters Fit

Apatero's saved characters organize named reference images. That helps keep source assets available; it does not establish a hard identity lock or a regional multi-character engine. Check which references the selected generation path accepts and supplies.

A saved reference can be useful in an individual-character workflow before compositing. A scene containing both characters needs its own review. The practical stopping point is an image that meets your recorded criteria, with the source files and edits retained so you can repeat or revise the work.