--- 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

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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**. ![teaser](assets/teaser.png?raw=true) ## 📚 Citation If you find our paper or this codebase useful for your research, please cite us. ```BibTeX @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}, } ```