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Wan Dancer AI Video Generator
Feed one portrait plus a song to the Wan Dancer AI Video Generator for a beat-locked 720p dance clip that stays sharp past a full minute.
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Inside Wan Dancer: How a Still Photo Learns to Dance
Built by Alibaba Tongyi Lab, the Wan Dancer AI Video Generator pairs a reference portrait with an audio clip and renders a complete routine — 720p, 30fps and rhythm-locked for well over a minute, with no motion capture gear involved.
- Choreography That Follows the BeatThe soundtrack drives every step — motion is read from the audio waveform and matched to the rhythm instead of looping a canned sequence.
- One Photo, One Consistent DancerFace, hair and outfit stay recognizable from the opening frame to the closing pose, even across long takes.
- Stable Past the One-Minute MarkWhere typical diffusion models fall apart after roughly 20 seconds, this two-stage pipeline keeps the routine structurally sound for a full minute and beyond.
From Photo to Dance Clip in Three Steps
Upload a portrait, add a track and choose a style — the whole music-to-dance workflow takes just a few minutes.
Feature Set: What Powers Wan Dancer's Music-to-Dance Output
Open weights under Apache-2.0, five trained dance genres and ComfyUI support — everything here is engineered for long, beat-accurate, single-dancer clips.
Beat-Aware Motion Synthesis
Choreography is derived from the audio waveform itself, so steps land on the actual beat rather than a generic canned loop.
Long-Form Temporal Stability
A global-then-local two-stage pipeline keeps body structure intact far beyond the 20-second limit — long enough to cover an entire chorus.
Identity Kept From a Single Shot
The reference subject's face, hairstyle and clothing are tracked throughout the routine, so the dancer stays unmistakably the same person.
Crisp 720p, Smooth 30fps
Every clip renders in high definition at 30 frames per second, sized for TikTok, Reels and Shorts.
Trained on Five Dance Styles
Chinese classical, K-pop, street, tap and Latin are all covered, letting one reference image match a wide spread of musical moods.
Apache-2.0 Open Weights
Weights are published on Hugging Face and ModelScope, with ComfyUI integration and LoRA fine-tuning available for custom routines.
Wan Dancer AI Video Generator: Your Questions Answered
Everything people ask before their first render — inputs, clip length, dance genres, licensing and more.
What exactly is the Wan Dancer AI Video Generator?
It is Wan-Dancer-14B, an open-source model from Alibaba Tongyi Lab that reads a portrait plus an audio file and produces a rhythm-synced dance clip at 720p and 30fps — no motion capture suit required.
How does the music-to-dance pipeline actually work?
In two passes: a global stage listens to the entire track and sketches the choreography as keyframes, then a local stage refines movement frame by frame. Planning first is what keeps long routines from drifting.
What inputs do I need to get started?
A clear portrait (a vertical full-body shot works best), an audio or music file, and a short text prompt describing the dance style you want.
How long can the finished dance video be?
Generation is designed for minute-scale output and holds together well past the roughly 20-second point where most diffusion models begin to break down.
Which dance styles are supported?
Five were used in training — Chinese classical, K-pop, street, tap and Latin — and you select among them simply by writing your prompt.
Is it open source, and can I self-host?
Yes. Wan-Dancer-14B ships under Apache-2.0 on Hugging Face and ModelScope, complete with inference code, ComfyUI nodes and LoRA fine-tuning for bespoke choreography.
Turn a Single Portrait Into a Full Dance Routine
Upload a photo, drop in your favorite track and let the model handle every step — your first beat-synced dance clip is only a few clicks away.
