Vidu

How to Create AI Videos With a Reference Character with Vidu Q2 Subject Ref

Vidu Q2 Subject Ref accepts 1-7 character reference images per generation — the densest character-reference slot among the three models in this scenario. For an AI influencer producer keeping "Mia" identical across a 12-week content series, that 7-image character sheet (front, three-quarter, profile, full-body, hands, expression range) gives Vidu more identity vectors than any single-anchor model. The result is the strongest face/jaw/hairline lock across multiple shots, especially when wardrobe and location vary.

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Step-by-Step Guide

Build a 5-7 image character sheet first

Before opening Vidu, generate the character sheet on Nano Banana 2 (the strongest face-locker for the source images). Aim for 5-7 distinct angles and expressions: front portrait, three-quarter, profile, full-body, neutral expression, smiling expression, hands close-up. This sheet is the identity bedrock — Vidu will sample identity from every image you provide.

Load all 7 references into the Vidu Q2 Subject Ref node

On Astorie's canvas, drop the Vidu Q2 Subject Ref node and attach all 7 character images. Vidu accepts up to 7 — fewer is fine, but 7 is the maximum identity density. Pin the front portrait as the primary reference, the others fill in angles and expressions the prompt may invoke.

Write per-shot prompts that invoke specific reference angles

Vidu reads prompts in concert with references. For a profile shot of "Mia" walking, the prompt "profile shot, character walking left to right, soft daylight" tells Vidu to lean on the profile reference. For a front-facing dialogue shot, "medium close-up, character looks toward camera and speaks" leans on the front reference. Match prompt direction to the reference set.

Vary wardrobe and location with the same identity anchor

For a 12-week content series, the wardrobe and location vary per episode — but identity must lock. With 7 references loaded, vary only the wardrobe and environment language in the prompt: "Mia in red leather jacket, downtown street at night" → "Mia in cream sweater, autumn forest path" → "Mia in business casual, modern office." Identity stays anchored; the rest is creative variation.

Use Vidu V2V Pro for video reference + image reference combined

For a follow-up shot that needs to mirror a previous clip's motion (Mia tilts her head exactly the same way she did in episode 3), switch to Vidu V2V Pro — it merges video and image references in a single pass. Drop the previous motion clip as video reference + the same 7-image character sheet, and Vidu generates new footage with both motion and identity locked.

Save the canvas as a series template

Once the Vidu Q2 Subject Ref node is set with the 7-image character sheet, save the canvas as a "Mia series" template. Each new episode reuses the same canvas with the wardrobe + location prompt swapped. Identity reads identical across the series because the reference stack does not change. This is the workflow that turns a 12-week content series into a single canvas.

Prompt Examples

Wardrobe + location variation, identity locked by the 7-image reference stack. Note no description of Mia's face — Vidu reads that from the references.

Mia in red leather jacket, downtown street at night, neon signs reflect on wet pavement, slow forward dolly, 6 seconds

Profile-specific shot. Vidu samples the profile angle from the reference sheet.

Profile shot of Mia walking left to right, autumn forest path, soft afternoon light, slight handheld breathing, 5 seconds

Front-facing dialogue beat. Vidu pulls the front reference and its expression range.

Medium close-up of Mia looking toward camera, soft golden hour key light, ambient outdoor cafe sound, 4 seconds

Parameter Tips

Vidu Q2 Subject Ref accepts up to 7 reference images — load the maximum for the densest identity lock.

Build the character sheet on Nano Banana 2 first; it is the strongest source-image face-locker.

Vary wardrobe + location in prompts but never describe the character's face — Vidu reads that from references.

Save the canvas as a series template — reuse the same Vidu node + 7 references across episodes.

For motion mirroring across episodes, switch to Vidu V2V Pro to merge video + image references.

What to Expect

Vidu Q2 Subject Ref outputs 5-8 second clips at 1080p with the strongest character-identity lock among the three models on this page — the 7-image reference slot is the differentiator. Render times 90-150 seconds. Best for AI influencer episodic content, recurring spokesperson, or fashion/beauty catalogs where identity must hold across 12+ shots. For motion-mirroring across episodes use Vidu V2V Pro; for budget-tier reference work use Seedance 2 Omni; for choreographed tight action use Kling O3 Reference.

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Kling O3 Reference

Kling O3 Reference adds character reference images for consistent appearance across clips and supports voice control over individual elements. Sharing the Kling 3.0 backbone (native 4K, 16-bit HDR, Omni Native Audio), it is the right pick when an AI influencer or brand spokesperson needs to deliver lip-synced dialogue across multiple cuts at festival-grade detail. The reference is stronger than Vidu on choreographed tight action; less reference-dense than Vidu Q2 (Vidu accepts 7, Kling O3 Reference reads fewer with stricter ranking).

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ByteDance

Seedance 2.0

Seedance 2 Omni adds character reference images to a generation that already accepts up to 12 reference assets — a unique combo of identity lock plus broad multimodal context (audio reference, location reference, palette reference). For an AI influencer producer running high-volume content where each episode varies wardrobe, location, and mood while identity stays anchored, Seedance Omni delivers strong per-clip Sutui economics. It is the pragmatic middle option between Vidu Q2 (densest reference) and Kling O3 Reference (tightest choreography).