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VR-GS: A Physical Dynamics-Aware Interactive Gaussian Splatting System in Virtual Reality

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arxiv 2401.16663 v2 pith:NLW4RRK3 submitted 2024-01-30 cs.HC cs.CV

classification cs.HCcs.CV
keywords virtualrealitysystemvr-gscontentinteractivedynamicdynamics-aware
verification ladder T0 review T1 audit T2 compute T3 formal
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As consumer Virtual Reality (VR) and Mixed Reality (MR) technologies gain momentum, there's a growing focus on the development of engagements with 3D virtual content. Unfortunately, traditional techniques for content creation, editing, and interaction within these virtual spaces 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 in a Virtual Reality 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 Virtual Reality 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.Our project page is available at: https://yingjiang96.github.io/VR-GS/.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Hearing Hands: Generating Sounds from Physical Interactions in 3D Scenes

    cs.CV 2025-06 conditional novelty 6.0 of 10

    A rectified flow model conditioned on 3D hand trajectories and rendered scene video generates realistic hand-scene interaction sounds, with a human study finding near-chance discrimination (47% misclassified).

  2. Enhancing non-Rigid 3D Model Deformations Using Mesh-based Gaussian Splatting

    cs.GR 2025-07 reject novelty 2.0 of 10

    A proposal to combine 3D Gaussian splatting, SAM segmentation, GS2Mesh conversion, LLM-based material assignment, and XPBD physics into a mesh-based editing pipeline, with no experimental validation.

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