DreaMoving: A Human Video Generation Framework based on Diffusion Models

December 08, 2023 · Entered Twilight · 🏛 arXiv.org

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Authors Mengyang Feng, Jinlin Liu, Kai Yu, Yuan Yao, Zheng Hui, Xiefan Guo, Xianhui Lin, Haolan Xue, Chen Shi, Xiaowen Li, Aojie Li, Xiaoyang Kang, Biwen Lei, Miaomiao Cui, Peiran Ren, Xuansong Xie arXiv ID 2312.05107 Category cs.CV: Computer Vision Citations 29 Venue arXiv.org Repository https://github.com/dreamoving/dreamoving ⭐ 1800 Last Checked 9 days ago

Abstract

In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos. Specifically, given target identity and posture sequences, DreaMoving can generate a video of the target identity moving or 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