AniCrafter: Customizing Realistic Human-Centric Animation via Avatar-Background Conditioning in Video Diffusion Models

• URL: http://arxiv.org/abs/2505.20255v2
• Date: Mon, 07 Jul 2025 17:56:30 GMT
• Title: AniCrafter: Customizing Realistic Human-Centric Animation via Avatar-Background Conditioning in Video Diffusion Models
• Authors: Muyao Niu, Mingdeng Cao, Yifan Zhan, Qingtian Zhu, Mingze Ma, Jiancheng Zhao, Yanhong Zeng, Zhihang Zhong, Xiao Sun, Yinqiang Zheng,
• Abstract summary: textbfAniCrafter is a diffusion-based human-centric animation model built on cutting-edge Image-to-Video (I2V) diffusion architectures.<n>Our model incorporates an innovative ''avatar-background'' conditioning mechanism that reframes open-domain human-centric animation as a restoration task.
• Score: 32.29517110097208
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recent advances in video diffusion models have significantly improved character animation techniques. However, current approaches rely on basic structural conditions such as DWPose or SMPL-X to animate character images, limiting their effectiveness in open-domain scenarios with dynamic backgrounds or challenging human poses. In this paper, we introduce \textbf{AniCrafter}, a diffusion-based human-centric animation model that can seamlessly integrate and animate a given character into open-domain dynamic backgrounds while following given human motion sequences. Built on cutting-edge Image-to-Video (I2V) diffusion architectures, our model incorporates an innovative ''avatar-background'' conditioning mechanism that reframes open-domain human-centric animation as a restoration task, enabling more stable and versatile animation outputs. Experimental results demonstrate the superior performance of our method. Codes are available at https://github.com/MyNiuuu/AniCrafter.

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