GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussians
Authors:
Top Cited Papers
- 16 June 2024
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 20299-20309
Abstract
We introduce GaussianAvatars 1 1 Project page: https://shenhanqian.github.io/gaussian-avatars, 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 dis-placement 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 reen-actments from a driving video, where our method outperforms existing works by a significant margin.Keywords
All Related Versions
This publication has 44 references indexed in Scilit:
- Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis2024
- TensoRF: Tensorial Radiance Fields2022
- Neural Strands: Learning Hair Geometry and Appearance from Multi-view Images2022
- Space-time Neural Irradiance Fields for Free-Viewpoint Video2021
- D-NeRF: Neural Radiance Fields for Dynamic Scenes2021
- Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction2021
- pixelNeRF: Neural Radiance Fields from One or Few Images2021
- The Unreasonable Effectiveness of Deep Features as a Perceptual Metric2018
- Face2Face: Real-Time Face Capture and Reenactment of RGB Videos2016
- A 3D Face Model for Pose and Illumination Invariant Face Recognition2009