GS-Verse: Mesh-based Gaussian Splatting for Physics-aware Interaction in Virtual Reality

• URL: http://arxiv.org/abs/2510.11878v2
• Date: Tue, 04 Nov 2025 18:24:59 GMT
• Title: GS-Verse: Mesh-based Gaussian Splatting for Physics-aware Interaction in Virtual Reality
• Authors: Anastasiya Pechko, Piotr Borycki, Joanna Waczyńska, Daniel Barczyk, Agata Szymańska, Sławomir Tadeja, Przemysław Spurek,
• Abstract summary: Current techniques for physically manipulating 3D content within Virtual Reality (VR) often face significant limitations.<n>We introduce GS-Verse, a novel method designed to overcome these challenges by directly integrating an object's mesh with a Gaussian Splatting representation.<n>Our system is designed to be physics-engine-agnostic, granting developers robust deployment flexibility.
• Score: 1.2271175670122132
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As the demand for immersive 3D content grows, the need for intuitive and efficient interaction methods becomes paramount. Current techniques for physically manipulating 3D content within Virtual Reality (VR) often face significant limitations, including reliance on engineering-intensive processes and simplified geometric representations, such as tetrahedral cages, which can compromise visual fidelity and physical accuracy. In this paper, we introduce GS-Verse (Gaussian Splatting for Virtual Environment Rendering and Scene Editing), a novel method designed to overcome these challenges by directly integrating an object's mesh with a Gaussian Splatting (GS) representation. Our approach enables more precise surface approximation, leading to highly realistic deformations and interactions. By leveraging existing 3D mesh assets, GS-Verse facilitates seamless content reuse and simplifies the development workflow. Moreover, our system is designed to be physics-engine-agnostic, granting developers robust deployment flexibility. This versatile architecture delivers a highly realistic, adaptable, and intuitive approach to interactive 3D manipulation. We rigorously validate our method against the current state-of-the-art technique that couples VR with GS in a comparative user study involving 18 participants. Specifically, we demonstrate that our approach is statistically significantly better for physics-aware stretching manipulation and is also more consistent in other physics-based manipulations like twisting and shaking. Further evaluation across various interactions and scenes confirms that our method consistently delivers high and reliable performance, showing its potential as a plausible alternative to existing methods.

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