DreaMoving: A Human Dance Video Generation Framework based on Diffusion Models

Mengyang Feng, Liu, Kai Yu, Yuan Yao, Zheng HUI, Xiefan Guo, lin, Haolan Xue, Chen Shi, Xiaowen Li, li, Miaomiao Cui, Peiran REN, Xuansong Xie

DreaMoving: A Human Dance Video Generation Framework based on Diffusion Models: 39 upvotes on Hugging Face Daily Papers, #2 of 8 papers on 2023-12-11. Day-by-day upvote history.

In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human dance videos. Specifically, given target identity and posture sequences, DreaMoving can generate a video of the target identity dancing anywhere driven by the posture sequences. To this end, we propose a Video ControlNet for motion-controlling and a Content Guider for identity preserving. The proposed model is easy to use and can be adapted to most stylized diffusion models to generate diverse results. The project page is available at https://dreamoving.github.io/dreamoving.

Paper page on Hugging Face · arXiv

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