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Jagiellonian University and others propose DomeGS: using 3D Gaussian splatting to complete the background of outdoor VR scenes

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Researchers from institutions including Jagiellonian University in Poland and the University of Cambridge in the UK published a paper on arXiv, proposing the DomeGS framework, which combines generative background completion with 3D Gaussian splatting (3DGS) scene reconstruction to address the missing sky, horizon, and distant views in outdoor VR scenes. 36 participants used Meta Quest Pro to test four groups of outdoor scenes. DomeGS achieved statistically significant improvements in spatial presence and perceived realism (p=0.042), and 75% of participants were more willing to stay for extended periods in virtual environments using DomeGS. The two approaches showed no significant differences in task completion time, head movement distance, or VR sickness symptom scores.

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On October 27, researchers from institutions including Jagiellonian University in Poland and the University of Cambridge in the UK published a paper on arXiv titled "DomeGS: Perceptually Consistent Background Completion for Unbounded 3D Gaussian Splatting in Virtual Reality," proposing a 3D scene background completion framework called DomeGS, aimed at solving the problem of missing sky, horizon, and distant content when reconstructing outdoor VR scenes with 3D Gaussian Splatting (3DGS).

It is understood that 3DGS can reconstruct high-fidelity 3D scenes from image data and supports real-time rendering, but when reconstructing large-scale outdoor environments, due to the lack of sufficient parallax and geometric information for distant objects, problems such as missing sky, discontinuous scene edges, or floating artifacts are prone to occur, affecting the user's immersive experience in VR environments.

Traditional VR applications usually use a Skybox or Skydome to fill in distant views, but such independent background solutions may produce differences in color, lighting, and perspective from the near-field content reconstructed by 3DGS, and are especially likely to expose visual seam issues when the user moves their viewpoint.

To address this limitation, the research team proposed the DomeGS framework, which combines generative background completion with 3DGS scene reconstruction, making the sky and distant views directly part of a unified 3D scene.

Technically, DomeGS first extracts panoramic images from an existing 3DGS scene and uses a generative model to complete the missing sky and distant content; it then generates new multi-view training data based on the scene's geometric structure and adds and optimizes Gaussian primitives within a spherical region of limited radius, ultimately fusing the completed background with the original 3D scene.

Unlike traditional skyboxes, DomeGS can present motion parallax that better matches spatial depth relationships when the user moves, while improving visual continuity between near and far views and reducing issues such as background seams and lighting inconsistency.

In terms of experiments, the research team recruited 36 participants and used the Meta Quest Pro headset to test four groups of outdoor scenes, comparing the experience differences between DomeGS and the traditional skybox solution.

The results showed that DomeGS achieved statistically significant improvements in both spatial presence and perceived realism (p=0.042). In a subjective preference survey, 75% of participants said they were more willing to stay for a long time in a virtual environment using DomeGS, and 69.4% of participants considered it more suitable for panoramic scene viewing.

In addition, the two solutions showed no significant differences in task completion time, head movement distance, or VR motion sickness symptom scores, indicating that while DomeGS improves scene realism, it did not bring significantly increased operational burden or discomfort in this experiment.

The research team believes that DomeGS provides a new technical path for background completion of 3DGS outdoor scenes and helps improve the quality of VR content based on real-environment reconstruction. However, the related results are still at the research stage, and their performance in more complex scenes and practical applications remains to be further verified.

Source: arXiv

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