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.

翻译：我们提出VRGaussianAvatar，一种集成系统，仅利用头戴式显示器（HMD）追踪信号即可在虚拟现实中实现实时的全身三维高斯泼溅（3DGS）化身。该系统采用包含VR前端和GA后端的并行流水线。VR前端通过逆运动学估计全身姿态，并将所得姿态与立体相机参数一同传输至后端。GA后端以立体方式渲染从单张图像重建的3DGS化身。为提升立体渲染效率，我们引入双眼批处理技术，该技术在单次批处理中联合处理左右眼视图，以减少冗余计算并支持高分辨率VR显示。我们通过量化性能测试和受试者内用户研究，将VRGaussianAvatar与基于图像和视频的网格化身基线进行对比评估。结果表明，VRGaussianAvatar能维持交互式VR性能，并在外观相似性、具身感和可信度方面获得更高评分。项目页面和源代码见https://vrgaussianavatar.github.io。