scenario-marketing
Vidu Reference-To-Video Q1 | Image-To-Video With Multi-Entity Consistency | WaveSpeedAI
Generate videos from reference images while keeping characters, objects, and scene identity consistent using Multi-Entity Consistency. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
Your request will cost $0.4 per run.
For $10 you can run this model approximately 25 times.
ExamplesView all
README
Vidu Reference-to-Video Q1
Vidu Reference-to-Video Q1 generates high-quality 5-second videos guided by multiple reference images. It combines advanced appearance preservation and motion synthesis, allowing creators to animate characters, products, or scenes while maintaining their original identity and style.
🌟 Key Features
🔁 Multi-Entity Consistency
- Preserves the visual identity, color tone, and texture of all reference subjects.
- Supports consistent appearance across dynamic motion sequences.
- Ideal for animating characters, fashion items, or branded products.
🧩 Flexible Input Options
- Accepts 1–7 reference images to define the subject, outfit, or style.
- Supports aspect ratios 16:9, 9:16, and 1:1.
- Adjustable movement amplitude (auto, small, medium, large) for customized motion intensity.
🎥 Cinematic Motion Generation
- Adds smooth camera motion and ambient scene transitions.
- Creates realistic parallax effects and subject movement.
- Works well with both portraits and product shots.
⚙️ Requirements
Images
- Count: 1–7 reference images
- Formats: PNG, JPEG, JPG
- Aspect ratio: Between 1:4 and 4:1
- Max file size: 50 MB per image
Prompt
-
Max length: 1500 characters
-
Describe desired motion, scene, or style.
Example: “The girl in image 2 wears the glasses from image 1 and walks through a sunny street, soft natural light, cinematic color tone.”
💰 Price
| Duration | Resolution | Cost per job |
|---|---|---|
| 5 seconds | 720p | $0.40 |
💡 Best Practices
- Use clear, high-resolution reference images for optimal appearance consistency.
- Describe the desired motion and scene context in detail.
- Experiment with movement amplitude to adjust animation style.
- Include multiple reference images for complex scenes or multi-object compositions.
- Keep visual themes consistent (lighting, color palette, resolution).
⚠️ Effect Boundaries
- Works best with realistic, well-lit images.
- Overly stylized or low-quality inputs may cause flickering or distortion.
- Movement amplitude directly affects scene dynamics and smoothness.
- Complex multi-character prompts may require more references for stability.
📝 Notes
- Make sure each uploaded image is accessible and properly formatted.
- Check that the prompt and image order correspond correctly (e.g., “image 1,” “image 2”).
- If outputs look inconsistent, simplify the scene or reduce reference count.
- Simple, focused prompts yield the best alignment and motion results.