Introducing Vidu Reference To Video Q1 on WaveSpeedAI

Introducing Vidu Reference-to-Video Q1 on WaveSpeedAI

The AI video generation landscape just took a significant leap forward. We’re excited to announce that Vidu Reference-to-Video Q1 is now available on WaveSpeedAI, bringing industry-leading multi-entity consistency technology to creators, marketers, and developers worldwide.

Developed by ShengShu Technology in collaboration with Tsinghua University—one of the pioneering teams in diffusion probability model research since 2022—Vidu Q1 represents a breakthrough in maintaining visual identity across AI-generated video content. Whether you’re animating characters, showcasing products, or creating branded content, this model ensures your subjects look exactly as intended throughout every frame.

What is Vidu Reference-to-Video Q1?

Vidu Reference-to-Video Q1 is a multimodal AI video generation model that creates high-quality 5-second videos guided by reference images. Unlike traditional text-to-video tools that struggle with consistency, this model uses advanced semantic understanding to preserve the visual identity, color tone, and texture of every subject you define.

The technology builds on ShengShu’s U-ViT architecture, which predates even the diffusion transformer (DiT) approach used by other major AI video platforms. This architectural foundation enables Vidu Q1 to understand not just what your reference images show, but how they relate to your text prompts—automatically generating and integrating elements described in your prompt even when they’re not present in the source images.

As Luo Yihang, CEO at ShengShu Technology, stated when announcing the multi-reference update: “This update breaks through the limits of what creators thought they could do with AI video. We’re getting closer to enabling users to create fully realized scenes, complete with a detailed cast of characters, objects, and backgrounds.”

Key Features

Multi-Entity Consistency

The headline feature of Vidu Q1 is its ability to maintain perfect visual consistency across dynamic motion sequences. Upload references for multiple subjects—characters, products, environments—and the model preserves each one’s appearance, texture, and color palette throughout the generated video. This technology was described as an “industry-first” when Vidu 1.5 introduced it, and Q1 takes it even further.

Flexible Multi-Image Input

Support for 1 to 7 reference images per generation gives you unprecedented control over complex scenes. Build visually rich compositions featuring multiple characters, props, or backgrounds without ever needing them in the same room during capture. Each image can define a different element of your final video.

Intelligent Semantic Understanding

The enhanced semantic understanding engine is what sets Vidu Q1 apart. By comprehending the relationship between your reference images and text prompts, the model can infer missing visual elements. For example, you might upload images of a person and a cityscape, then prompt: “The person plays a guitar while walking through the city at sunset.” Even without a guitar reference, Vidu Q1 generates and integrates the instrument seamlessly while maintaining visual consistency.

Cinematic Motion Generation

Every output features smooth camera motion, ambient scene transitions, and realistic parallax effects. The model adds professional-grade movement that transforms static references into dynamic, engaging video content suitable for commercial use.

Customizable Motion Intensity

Fine-tune your results with adjustable movement amplitude options: auto, small, medium, or large. This control lets you match the animation style to your specific project requirements, whether you need subtle product rotations or dramatic character movements.

Real-World Use Cases

E-Commerce Product Videos

According to HubSpot research, 88% of consumers have been convinced to buy a product after watching a brand’s video. Vidu Reference-to-Video Q1 enables e-commerce brands to create compelling product showcases at scale. Upload product images from multiple angles, describe the scene you want, and generate professional video content without traditional production costs. Companies using AI for video creation report completing projects up to 60% faster than traditional methods.

Brand Marketing Campaigns

Maintain character and brand element consistency across entire advertising campaigns. Use the same reference images to generate multiple videos with different scenarios, ensuring your brand mascot, spokesperson, or product appears identical in every piece of content—a capability that previously required expensive VFX work.

The speed and affordability of AI-generated video make it ideal for the constant content demands of social media marketing. Create variations of product videos, character animations, or branded content rapidly while maintaining the visual consistency that builds brand recognition.

Animation and Storytelling

Creators can develop characters and scenes that persist across multiple video generations. This opens possibilities for serialized content, animated series concepts, or storyboard-to-video workflows where visual continuity is essential.

Fashion and Apparel

Animate clothing on models, showcase accessories in motion, or create lookbook videos that highlight texture and movement. The multi-reference capability means you can combine garment images, model references, and scene backgrounds into cohesive fashion content.

Getting Started on WaveSpeedAI

Accessing Vidu Reference-to-Video Q1 through WaveSpeedAI takes just minutes:

Visit the model page at wavespeed.ai/models/vidu/reference-to-video-q1
Upload your reference images (1-7 images in PNG, JPEG, or JPG format)
Write your prompt describing the desired motion, scene, and style (up to 1,500 characters)
Select your aspect ratio (16:9, 9:16, or 1:1) and movement amplitude
Generate your 5-second, 720p video

Pricing is straightforward: $0.40 per 5-second video generation. With WaveSpeedAI’s infrastructure, you get fast inference speeds, no cold starts, and reliable availability—meaning you can iterate quickly on your creative projects without waiting for infrastructure to spin up.

Tips for Best Results

Use clear, high-resolution reference images with consistent lighting
Number your images in prompts (e.g., “the person in image 1 wears the jacket from image 2”)
Start with simpler scenes and fewer references before attempting complex multi-entity compositions
Experiment with movement amplitude to find the right energy for your content

Conclusion

Vidu Reference-to-Video Q1 represents a genuine advancement in what’s possible with AI video generation. The combination of multi-entity consistency, semantic understanding, and flexible reference input addresses what has long been the Achilles’ heel of AI video: maintaining visual identity across frames and scenes.

For creators and businesses looking to scale video production without sacrificing quality or consistency, this model offers a practical path forward. Whether you’re generating product videos, brand content, or creative projects, the ability to define exactly how subjects appear—and trust that the AI will maintain that definition—changes what’s achievable.

Ready to create consistent, professional AI video content? Try Vidu Reference-to-Video Q1 on WaveSpeedAI today and experience the difference that true multi-entity consistency makes.