用头显追踪信号实时生成3D高斯肖像，提升虚拟现实中的形象还原度。
VRGaussianAvatar: Integrating 3D Gaussian Avatars into VR
- 通过逆运动学估算全身姿态，前后端协同实现低延迟渲染
- 采用双目批处理技术，减少冗余计算，支持高分辨率显示
- 用户实验表明形象相似度与沉浸感显著优于传统方法
我们提出VRGaussianAvatar，一个集成系统，仅使用头戴式显示器（HMD）追踪信号即可在虚拟现实中实现实时全身体积高斯溅射（3DGS）肖像。该系统采用并行架构，包含VR前端和GA后端。VR前端利用逆运动学估计全身姿态，并将姿态信息与立体相机参数传至后端；GA后端基于单张图像重建的3DGS肖像进行立体渲染。为提升立体渲染效率，我们引入双目批处理（Binocular Batching），在一次批处理中联合处理左右眼视图，减少冗余计算，支持高分辨率VR显示。我们在定量性能测试和被试内用户研究中评估了VRGaussianAvatar，对比了基于图像和视频的网格肖像基线。结果表明，该系统维持了交互式虚拟现实性能，并在感知外观相似性、具身感和合理性方面表现更优。项目页面与源代码见https://vrgaussianavatar.github.io。
原文摘要 · Abstract (English)
We present VRGaussianAvatar, an integrated system that enables real-time full-body 3D Gaussian Splatting (3DGS) avatars in virtual reality using only head-mounted display (HMD) tracking signals. The system adopts a parallel pipeline with a VR Frontend and a GA Backend. The VR Frontend uses inverse kinematics to estimate full-body pose and streams the resulting pose along with stereo camera parameters to the backend. The GA Backend stereoscopically renders a 3DGS avatar reconstructed from a single image. To improve stereo rendering efficiency, we introduce Binocular Batching, which jointly processes left and right eye views in a single batched pass to reduce redundant computation and support high-resolution VR displays. We evaluate VRGaussianAvatar with quantitative performance tests and a within-subject user study against image- and video-based mesh avatar baselines. Results show that VRGaussianAvatar sustains interactive VR performance and yields higher perceived appearance similarity, embodiment, and plausibility. Project page and source code are available at https://vrgaussianavatar.github.io.
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