One Shot, One Talk: Whole-body Talking Avatar from a Single Image

• URL: http://arxiv.org/abs/2412.01106v1
• Date: Mon, 02 Dec 2024 04:27:41 GMT
• Title: One Shot, One Talk: Whole-body Talking Avatar from a Single Image
• Authors: Jun Xiang, Yudong Guo, Leipeng Hu, Boyang Guo, Yancheng Yuan, Juyong Zhang,
• Abstract summary: Building realistic and animatable avatars still requires minutes of multi-view or monocular self-rotating videos. We propose a novel pipeline that tackles two critical issues: 1) complex dynamic modeling and 2) generalization to novel gestures and expressions. Our method enables the creation of a photorealistic, precisely animatable, and expressive whole-body talking avatar from just a single image.
• Score: 28.932709370417232
• License:
• Abstract: Building realistic and animatable avatars still requires minutes of multi-view or monocular self-rotating videos, and most methods lack precise control over gestures and expressions. To push this boundary, we address the challenge of constructing a whole-body talking avatar from a single image. We propose a novel pipeline that tackles two critical issues: 1) complex dynamic modeling and 2) generalization to novel gestures and expressions. To achieve seamless generalization, we leverage recent pose-guided image-to-video diffusion models to generate imperfect video frames as pseudo-labels. To overcome the dynamic modeling challenge posed by inconsistent and noisy pseudo-videos, we introduce a tightly coupled 3DGS-mesh hybrid avatar representation and apply several key regularizations to mitigate inconsistencies caused by imperfect labels. Extensive experiments on diverse subjects demonstrate that our method enables the creation of a photorealistic, precisely animatable, and expressive whole-body talking avatar from just a single image.

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