Keeping character consistency in AI video projects
Learn how reusable character references, model notes, and asset libraries help keep AI video characters visually consistent.
TL;DR
Character consistency in AI video requires 3 things: a standardized reference image set (front/side/back), consistent prompt templates that reference the same character traits, and an asset library that stores all character generations in one place.
Create a character reference first
Before generating scenes, define the character appearance, clothing, mood, and visual style. Generate front, side, and back views. Store the result as a reusable reference asset. This is the single highest-ROI step for character consistency.
Reuse assets across scenes
Consistency improves when each scene starts from the same reference library instead of rewriting prompts from scratch. Load the character reference image into each image-to-video or image generation step.
Prompt template for consistency
Use this template: "[Character name], [key physical traits], wearing [clothing description], [mood/expression], [lighting], [camera angle], consistent with reference image." Change only the action and scene context between generations.
What models work best
For character reference generation: Standard Image (20 SP) or Advanced Image/Edit (50 SP). For character-to-video: Wan 2.7 (30 SP/5s) for tests, Seedance 2.0 (450 SP/5s) for final output. Text models (DeepSeek V4, 1 SP) help refine character descriptions.
Limitations
No AI model in mid-2026 achieves perfect character consistency across multiple video clips. Expect subtle variations in facial features, clothing details, and proportions. Manual compositing or editing may still be needed. Character consistency is strongest when using the same model and similar prompts across all generations.