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Wan Dancer AI Video Generator
Upload a single portrait and any music track to instantly produce a beat-synced dance video. Powered by Alibaba Tongyi Lab's open-source model, this tool delivers 720p at 30fps, maintains motion coherence for over a minute, and requires no motion capture equipment.
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Why Choose This Music-to-Dance AI Tool
Developed by Alibaba Tongyi Lab, this model (Wan-Dancer-14B) takes a reference photo plus an audio file and outputs a fully choreographed dance video at 720p and 30fps. The motion locks to the rhythm and remains structurally coherent for over a full minute, all without any motion capture hardware.
- Audio-Driven Movement GenerationThe system analyzes your music waveform to produce dance sequences that hit every beat precisely.
- Consistent Subject IdentityUsing just one portrait, the tool preserves facial features, hair, and clothing throughout the entire dance clip.
- Extended Temporal StabilityUnlike most diffusion models that falter after 20 seconds, this engine maintains smooth motion for a full minute or more.
Step-by-Step Guide to Using This Dance Video Creator
Create a rhythm-synced dance video from a photo and a song in just three straightforward steps.
Core Capabilities of the Music-to-Dance Generator
An open-weights model designed for long-form, rhythm-locked, single-subject dance generation — supporting multiple genres, ComfyUI integration, and Apache-2.0 licensing.
Waveform-Driven Dance Synthesis
Derives motion directly from audio waveforms, ensuring every step matches the actual beat rather than looping generic moves.
Extended Temporal Stability
A two-stage global-to-local pipeline keeps the dance structurally sound well past the typical 20-second limit, covering full song choruses.
Single-Image Identity Retention
Tracks the subject's face, hairstyle, and outfit throughout the entire clip, maintaining visual consistency from start to finish.
HD Output at Smooth Frame Rate
Produces high-definition clips at 30 frames per second, optimized for platforms like TikTok, Instagram Reels, and YouTube Shorts.
Five Dance Styles Supported
Trained on Chinese classical, K-pop, street, tap, and Latin — the model adapts to diverse musical moods from a single reference image.
Open Source Under Apache-2.0
Released on Hugging Face and ModelScope with full inference code, ComfyUI support, and LoRA fine-tuning for custom routines.
Frequently Asked Questions About the Music-to-Dance Generator
Find answers to the most common queries regarding this AI dance video creation tool.
What exactly is this music-to-dance model?
It's an open-source model (Wan-Dancer-14B) from Alibaba Tongyi Lab that converts a single portrait and any music file into a beat-synced dance video at 720p and 30fps, without requiring any motion capture equipment.
How does the technology work behind the scenes?
It employs a two-stage pipeline: a global stage analyzes the entire music track and plans choreography as keyframes, then a local stage refines each frame's motion. This planning-first approach ensures long dances remain coherent.
What inputs are needed to generate a dance video?
You'll need a clear portrait photo (a vertical full-body shot works best), a music or audio file, and a short text prompt describing the desired dance style.
What is the maximum video length it can produce?
The model is designed for minute-scale generation and maintains coherence well past the roughly 20-second mark where most diffusion models fail.
Which dance styles are available?
It's trained on five genres: Chinese classical, K-pop, street, tap, and Latin. You specify the style via your text prompt.
Is the model truly open source?
Yes, Wan-Dancer-14B is distributed under Apache-2.0 on Hugging Face and ModelScope, with full inference code, ComfyUI integration, and LoRA fine-tuning support for custom choreography.
Start Creating Beat-Synced Dance Videos Now
Upload a photo and a song to instantly generate a rhythm-locked dance video with this AI-powered tool.