README.md

metadata

license: apache-2.0
datasets:
  - MCG-NJU/X-Dance
base_model:
  - Wan-AI/Wan2.1-I2V-14B-480P
pipeline_tag: image-to-video
library_name: diffusers

SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame Preservation

Jiaming Zhang · Shengming Cao · Rui Li · Xiaotong Zhao · Yutao Cui
Xinglin Hou · Gangshan Wu · Haolan Chen · Yu Xu · Limin Wang · Kai Ma


Multimedia Computing Group, Nanjing University   |   Platform and Content Group (PCG), Tencent

This repository is the checkpoint of paper "SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame Preservation". SteadyDancer is a strong animation framework based on Image-to-Video paradigm, ensuring robust first-frame preservation. In contrast to prior Reference-to-Video approaches that often suffer from identity drift due to spatio-temporal misalignments common in real-world applications, SteadyDancer generates high-fidelity and temporally coherent human animations, outperforming existing methods in visual quality and control while requiring significantly fewer training resources.

📚 Citation

If you find our paper or this codebase useful for your research, please cite us.

@misc{zhang2025steadydancer,
      title={SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame Preservation}, 
      author={Jiaming Zhang and Shengming Cao and Rui Li and Xiaotong Zhao and Yutao Cui and Xinglin Hou and Gangshan Wu and Haolan Chen and Yu Xu and Limin Wang and Kai Ma},
      year={2025},
      eprint={2511.19320},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2511.19320}, 
}