ลด 50% โมเดล Vidu Q3 และ Q3 Pro · เฉพาะที่ WaveSpeedAI | 20 พ.ค. – 2 มิ.ย.

Vidu Reference to Video Q2

vidu /

Vidu Q2 is an Image-to-Video and Reference-to-Video model that emphasizes subtle facial expressions and smooth push-pull camera moves for natural motion. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-video
อินพุต

ลากและวางหรือคลิกเพื่ออัปโหลด

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ลากและวางหรือคลิกเพื่ออัปโหลด

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ว่าง

$0.1ต่อครั้ง·~10 / $1

ต่อไป:

ตัวอย่างดูทั้งหมด

A dramatic cinematic scene. Iron Man in image 1 and Batman in image 2 stand facing each other on a rain-slicked Gotham City rooftop at a dark, stormy midnight. Heavy rain lashes down, illuminated by frequent, blinding flashes of lightning that momentarily silhouette their iconic forms. Thunder rumbles ominously in the background. The atmosphere is extremely tense, charged with an impending clash. They hold their stances, eyes locked, rain streaming down their suits. Suddenly, in a synchronized, powerful motion, both Iron Man and Batman simultaneously launch a fierce punch towards each other. Iron Man's repulsor gauntlet begins to glow with blue energy, while Batman's fist is clenched, muscles taut. The moment of impact is frozen briefly, sparks or rain splashing violently from their fists.

First, the man in image 1 is smiling and talking to someone off-camera. He spots the man in image 2 walking towards him. the man in image 1 smile immediately fades. His expression becomes visibly awkward, annoyed, and forced. He subtly rolls his eyes. the man in image 2, completely oblivious and with his usual stoic, humorless expression, approaches the man in image 1 and gives a single, curt, professional nod as a greeting. As the man in image 2 turns his head for a moment (perhaps looking at a reporter), the man in image 1 quickly turns his head to the side, away from the man in image 2. His brow is furrowed, and his mouth moves as he quietly mutters to himself in annoyance for one or two seconds.

The man in Figure 2 looks very comfortable and relaxed when sitting on the sofa in Figure 1. Advertising style, showing the comfort of the sofa

Let the woman in Picture 2 wear the armor of the character in Picture 2 and walk confidently on the stage.

Let the woman in Picture 2 hold the teddy bear in Picture 1 and act very happy.

A cinematic, photorealistic scene on a bustling, sun-drenched city street (like Paris or New York). The camera starts with a medium shot, following a beautiful woman in image 2 as she walks alone, perhaps looking at her phone or slightly lost in thought, unaware of her surroundings. From behind, a man (her boyfriend) in image 1 with a warm, knowing smile, quickly catches up to her. He gently taps her on the shoulder. The woman turns around, her face initially showing a look of slight annoyance or confusion. In the exact moment she recognizes him, her expression completely transforms. Her eyes go wide with pure, unadulterated, joyful surprise. A massive, radiant smile breaks out across her face, as if she can't believe he's really there. She lets out a happy gasp or laugh, and immediately throws her arms around his neck, leaping into his embrace. He catches her, lifting her slightly off the ground as he spins her in a tight hug. They immediately come together in a deep, passionate, and intense kiss, completely lost in their own world as the crowded sidewalk blurs around them in a beautiful bokeh. They hold their stances, eyes locked, rain streaming down their suits. Suddenly, in a synchronized, powerful motion, both Iron Man and Batman simultaneously launch a fierce punch towards each other. Iron Man's repulsor gauntlet begins to glow with blue energy, while Batman's fist is clenched, muscles taut. The moment of impact is frozen briefly, sparks or rain splashing violently from their fists.

The person from [Image 1] is wearing the bikini from [Image 2]. **CRITICAL:** She is wearing **only** the complete outfit from [Image 2]

Change the woman's clothes in picture 2 to the bikini in picture 1. Let the woman show off her clothes and body shape in a 360-degree like a fashion model. Slow motion, full body display, ensuring natural facial details and expressions

Change the woman's clothes in picture 2 to the bikini in picture 1. Let the woman show off her clothes and body shape like a fashion model. Slow motion, full body display, ensuring natural facial details and expressions

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README

Vidu Q2 Reference-to-Video

Vidu Q2 Reference-to-Video transforms one or multiple input images into expressive, cinematic videos. It excels at producing subtle facial motion, natural body dynamics, and camera-aware storytelling — ideal for turning still portraits or concept images into smooth motion clips.

Why Choose This?

  • Smooth motion realism Subtle micro-expressions, eye movements, and breathing motions reproduced authentically.

  • Cinematic camera dynamics Built-in control of push/pull, pan, tilt, and zoom effects for scene depth and emotional tone.

  • Multiple-image reference support Upload up to 7 reference images to guide pose, lighting, or perspective transitions.

  • Flexible composition Choose from multiple aspect ratios (16:9, 9:16, 4:3, 3:4, 1:1) for any platform.

  • Motion amplitude control Select auto, small, medium, or large to define the strength and style of movement.

  • High fidelity output Consistent lighting, identity preservation, and accurate reference adherence.

Parameters

ParameterRequiredDescription
promptYesDescribe the scene, action, or mood
imagesYesReference images (up to 7 images)
aspect_ratioNoAspect ratio: 16:9, 9:16, 4:3, 3:4, or 1:1
resolutionNoOutput resolution: 540p, 720p, or 1080p
durationNoVideo length in seconds (1–10)
movement_amplitudeNoMotion intensity: auto, small, medium, or large
seedNoRandom seed for reproducibility (-1 for random)

How to Use

  1. Upload reference images — add up to 7 images to guide the generation.
  2. Write your prompt — describe the scene, action, camera motion, or mood.
  3. Choose aspect ratio — select based on your target platform.
  4. Set resolution — 540p, 720p, or 1080p based on quality needs.
  5. Set duration — choose video length from 1 to 10 seconds.
  6. Adjust movement amplitude — auto for portraits, medium/large for action.
  7. Run — submit and download your video.

Pricing

ResolutionDurationPrice
540p1s$0.075
540p2s$0.10
540p3s$0.125
540p4s$0.15
540p5s$0.175
540p6s$0.20
540p7s$0.225
540p8s$0.25
540p9s$0.35
540p10s$0.45
720p1s$0.125
720p2s$0.15
720p3s$0.175
720p4s$0.20
720p5s$0.225
720p6s$0.25
720p7s$0.275
720p8s$0.30
720p9s$0.40
720p10s$0.50
1080p1s$0.375
1080p2s$0.425
1080p3s$0.475
1080p4s$0.525
1080p5s$0.575
1080p6s$0.625
1080p7s$0.675
1080p8s$0.725
1080p9s$0.825
1080p10s$0.925

Billing Rules

540p: $0.075 for 1s, +$0.025/s up to 8s, then $0.35 for 9s, $0.45 for 10s

720p: $0.125 for 1s, +$0.025/s up to 8s, then $0.40 for 9s, $0.50 for 10s

1080p: $0.375 for 1s, +$0.05/s up to 8s, then $0.825 for 9s, $0.925 for 10s

Best Use Cases

  • Filmmakers and Storytellers — Bring still characters or concept art to life with controlled, cinematic motion.
  • Advertising Creators — Generate short motion ads with precise control over composition and intensity.
  • Artists and Illustrators — Animate hand-drawn or AI-generated portraits into dynamic living forms.
  • Game and Animation Studios — Prototype visual narratives quickly using character or environment references.

Pro Tips

  • Use consistent lighting and angles among reference images for smoother transitions.
  • Write prompts that define camera motion, emotion, or scene tone clearly.
  • "auto" movement amplitude works best for portrait-style animation.
  • Use "medium" or "large" amplitude for full-body or action scenes.
  • For cinematic looks, pair 16:9 with 1080p and descriptive atmosphere prompts.

Notes

  • Maximum 7 reference images per generation.
  • Maximum duration is 10 seconds.
  • If using image URLs, ensure they are publicly accessible.
  • Successfully loaded images will display as thumbnails in the interface.

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Reference To Video Q2 API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/vidu/reference-to-video-q2 with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Reference To Video Q2 below.

HTTP example
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/vidu/reference-to-video-q2" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "aspect_ratio": "16:9",
    "resolution": "720p",
    "duration": 5,
    "movement_amplitude": "auto",
    "seed": 0
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].
Node.js example
// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("vidu/reference-to-video-q2", {
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "16:9",
        "resolution": "720p",
        "duration": 5,
        "movement_amplitude": "auto",
        "seed": 0
});

console.log(result.outputs[0]); // → URL of the generated output
Python example
# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "vidu/reference-to-video-q2",
    {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "aspect_ratio": "16:9",
    "resolution": "720p",
    "duration": 5,
    "movement_amplitude": "auto",
    "seed": 0
}
)

print(output["outputs"][0])  # → URL of the generated output

Reference To Video Q2 API — Frequently asked questions

What is the Reference To Video Q2 API?

Reference To Video Q2 is a Vidu model for video generation from images, exposed as a REST API on WaveSpeedAI. Vidu Q2 is an Image-to-Video and Reference-to-Video model that emphasizes subtle facial expressions and smooth push-pull camera moves for natural motion. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Reference To Video Q2 API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/vidu/vidu-reference-to-video-q2.

How much does Reference To Video Q2 cost per run?

Reference To Video Q2 starts at $0.10 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Reference To Video Q2 accept?

Key inputs: `prompt`, `images`, `aspect_ratio`, `resolution`, `duration`, `seed`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/vidu/vidu-reference-to-video-q2.

How long does Reference To Video Q2 take to generate?

Average end-to-end generation time on WaveSpeedAI is around 129 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Reference To Video Q2 outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Vidu). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.