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In this paper, we present DreaMoving, a diffusion-based controllable videogeneration framework to produce high-quality customized human videos.Specifically, given target identity and posture sequences, DreaMoving cangenerate a video of the target identity moving or dancing anywhere driven bythe posture sequences. To this end, we propose a Video ControlNet formotion-controlling and a Content Guider for identity preserving. The proposedmodel is easy to use and can be adapted to most stylized diffusion models togenerate diverse results. The project page is available athttps://dreamoving.github.io/dreamoving

DreaMoving: A Human Video Generation Framework based on Diffusion Models