VR-GS: A Physical Dynamics-Aware Interactive Gaussian Splatting System in Virtual Reality
Ying Jiang, Chang Yu, Tianyi Xie, Xuan Li, Yutao Feng, Huamin Wang, Minchen Li, Henry Y. K. Lau, Feng Gao, Yin Yang, Chenfanfu Jiang
Abstract
As 3D content becomes increasingly prevalent, there’s a growing focus on the development of engagements with 3D virtual content. Unfortunately, traditional techniques for creating, editing, and interacting with this content are fraught with difficulties. They tend to be not only engineering-intensive but also require extensive expertise, which adds to the frustration and inefficiency in virtual object manipulation. Our proposed VR-GS system represents a leap forward in human-centered 3D content interaction, offering a seamless and intuitive user experience. By developing a physical dynamics-aware interactive Gaussian Splatting (GS) in a Virtual Reality (VR) setting, and constructing a highly efficient two-level embedding strategy alongside deformable body simulations, VR-GS ensures real-time execution with highly realistic dynamic responses. The components of our system are designed for high efficiency and effectiveness, starting from detailed scene reconstruction and object segmentation, advancing through multi-view image in-painting, and extending to interactive physics-based editing. The system also incorporates real-time deformation embedding and dynamic shadow casting, ensuring a comprehensive and engaging virtual experience.
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Install the CLIlune papers fulltext 42d8cd64-25ea-4f0a-96da-251a0da2730dCited by top-tier papers78
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Builds on31
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- Neural Sparse Voxel FieldsLingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua et al.NeurIPS 2020 · 1,535 citations
- Nerfies: Deformable Neural Radiance FieldsKeunhong Park, Utkarsh Sinha, Jonathan T. Barron, Sofien Bouaziz et al.ICCV 2021 · 1,442 citations
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