Wan 2.7 References
Advanced video-to-video generation model that transforms existing footage using reference videos and optional reference images, featuring intelligent prompt expansion and high-resolution 1080p output with preserved temporal coherence.
Overview
Wan 2.7 References is a video generation model available on the GenVR platform. Advanced video-to-video generation model that transforms existing footage using reference videos and optional reference images, featuring intelligent prompt expansion and high-resolution 1080p output with preserved temporal coherence.
Key Features
- Video-to-video transformation with dual reference conditioning (video + optional images)
- Native 720p and 1080p high-resolution output support
- AI-powered prompt expansion for enhanced input descriptions
- Temporal consistency algorithms to prevent frame flickering
- Style and character migration from reference images to target video
- Multi-aspect ratio support (9:16, 16:9, 1:1, and cinematic formats)
- Motion preservation technology maintaining original camera dynamics
- Frame-level coherence optimization for smooth transitions
Popular Use Cases
- Product video restyling for seasonal marketing campaigns
- Virtual fashion try-on and apparel visualization on models
- Brand guideline application to existing video content libraries
- Character animation maintaining consistent identity across scenes
- Architectural visualization modifications and lighting adjustments
Best For
- Video production studios requiring style consistency across footage
- E-commerce marketers creating product video variations
- Content creators repurposing existing video assets
- Advertising agencies developing campaign visual variations
- Social media managers generating platform-specific video formats
Limitations to Keep in Mind
- Requires existing reference video input (not a text-to-video model)
- High GPU memory requirements for 1080p and longer duration videos
- Complex rapid motion scenes may exhibit temporal artifacts
- Style transfer quality heavily dependent on reference image clarity and relevance
- Processing time increases significantly with higher resolutions and frame counts
Why Choose This Model
- Reference-Guided Control: Transform existing videos while preserving original motion, composition, and camera movements
- Image Conditioning: Apply specific visual styles, characters, or aesthetics from reference images to maintain brand consistency
- High-Fidelity Output: Native 1080p resolution generation suitable for professional broadcast and commercial use
- Temporal Stability: Advanced motion-aware algorithms ensure flicker-free, coherent video sequences across all frames
- Prompt Intelligence: Automatic prompt expansion enhances simple descriptions into detailed generation instructions
- Structural Integrity: Maintain scene dynamics and spatial relationships while altering visual appearance
- Character Consistency: Lock subject identity across video frames using reference image guidance for avatar creation
- Flexible Workflow: Support for both video-only transformation and video-plus-image hybrid conditioning
- Format Versatility: Generate content optimized for mobile vertical, desktop horizontal, or cinematic widescreen displays
- Efficient Processing: Optimized inference pipeline for rapid video variation generation and batch processing
Alternatives on GenVR
- Seedance 2.0 Omni
- Vidu Q3 Pro
- Vidu Q2 I2V Turbo
Pricing
Billed through GenVR credits
720p: 100/150/200 credits for 5s/10s/15s. 1080p is 1.6x of 720p pricing.
Properties
Customizable parameters available for this model.
Required
Text description of the desired scene and action. Reference characters as "Video 1", "Video 2" etc.
Optional
Reference image URLs (max 5). Combined with videos, total must be 1-5.
One or more reference videos. Combined with reference images, total must be 1-5.
Optional reference image to supplement the video references.
Elements to exclude from the generated video.
Output resolution.
GenVR Visual App
Experience the power of Wan 2.7 References through our intuitive visual interface. Experiment with prompts, adjust parameters in real-time, and download your results instantly.
Launch AppDeveloper API Docs
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