VRGaussianAvatar: Integrating 3D Gaussian Avatars into VR
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arXiv
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| Format: | Preprint |
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2026
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| author | Song, Hail Yoon, Boram Yang, Seokhwan Kang, Seoyoung Kim, Hyunjeong Metzmacher, Henning Woo, Woontack |
| author_facet | Song, Hail Yoon, Boram Yang, Seokhwan Kang, Seoyoung Kim, Hyunjeong Metzmacher, Henning Woo, Woontack |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_01674 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | VRGaussianAvatar: Integrating 3D Gaussian Avatars into VR Song, Hail Yoon, Boram Yang, Seokhwan Kang, Seoyoung Kim, Hyunjeong Metzmacher, Henning Woo, Woontack Computer Vision and Pattern Recognition Graphics 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. |
| title | VRGaussianAvatar: Integrating 3D Gaussian Avatars into VR |
| topic | Computer Vision and Pattern Recognition Graphics |
| url | https://arxiv.org/abs/2602.01674 |