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Computer Science > Computer Vision and Pattern Recognition

arXiv:2312.02069 (cs)
[Submitted on 4 Dec 2023 (v1), last revised 28 Mar 2024 (this version, v2)]

Title:GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussians

Authors:Shenhan Qian, Tobias Kirschstein, Liam Schoneveld, Davide Davoli, Simon Giebenhain, Matthias Nießner
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Abstract:We introduce GaussianAvatars, a new method to create photorealistic head avatars that are fully controllable in terms of expression, pose, and viewpoint. The core idea is a dynamic 3D representation based on 3D Gaussian splats that are rigged to a parametric morphable face model. This combination facilitates photorealistic rendering while allowing for precise animation control via the underlying parametric model, e.g., through expression transfer from a driving sequence or by manually changing the morphable model parameters. We parameterize each splat by a local coordinate frame of a triangle and optimize for explicit displacement offset to obtain a more accurate geometric representation. During avatar reconstruction, we jointly optimize for the morphable model parameters and Gaussian splat parameters in an end-to-end fashion. We demonstrate the animation capabilities of our photorealistic avatar in several challenging scenarios. For instance, we show reenactments from a driving video, where our method outperforms existing works by a significant margin.
Comments: Project page: this https URL
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2312.02069 [cs.CV]
  (or arXiv:2312.02069v2 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2312.02069

Submission history

From: Shenhan Qian [view email]
[v1] Mon, 4 Dec 2023 17:28:35 UTC (3,668 KB)
[v2] Thu, 28 Mar 2024 15:51:05 UTC (3,628 KB)
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