NSFW Wan 2.7 Reference-to-Video
Wan 2.7 Reference-to-Video generates new video scenes guided by reference videos and an optional reference image, maintaining consistent characters, styles, and visual identity. Upload one or more reference videos, describe the scene you want, and the model produces a coherent, character-consistent video that brings your references into a new context.
Why Choose This?
Multi-video reference support Upload multiple reference videos to combine characters or visual elements from different sources into a single new scene.
Character-consistent generation The model preserves the identity, appearance, and style of characters from your reference videos throughout the generated clip.
Optional reference image Provide an additional still image to further guide the visual composition or introduce a new element.
Resolution options Generate at 720p or 1080p to match your delivery requirements.
How to Use
Write your prompt — describe the new scene, referencing characters by position.
Upload reference image (optional) — provide a still image to supplement the visual references.
Add negative prompt (optional) — specify elements you want to exclude from the output.
Select resolution — 720p for standard output, 1080p for higher-quality results.
Select aspect ratio — choose the format that fits your target platform.
Set duration — choose your desired clip length in seconds.
Set seed (optional) — fix the seed to reproduce a specific result in future runs.
Submit — generate, preview, and download your video.
Best Use Cases
Character-Driven Storytelling — Place characters from multiple reference videos into entirely new scenarios.
Fan Content & IP Crossovers — Combine characters from different sources into a single coherent scene.
Marketing & Brand Video — Generate new scenes featuring consistent brand characters or spokespeople from reference footage.
Creative Concepting — Rapidly prototype multi-character scenes for pitching and storyboarding.
Social Media Content — Create novel, character-consistent short-form video from existing footage.
