VR-Splatting: Foveated Radiance Field Rendering via 3D Gaussian Splatting and Neural Points (2410.17932v2)

Abstract: Recent advances in novel view synthesis have demonstrated impressive results in fast photorealistic scene rendering through differentiable point rendering, either via Gaussian Splatting (3DGS) [Kerbl and Kopanas et al. 2023] or neural point rendering [Aliev et al. 2020]. Unfortunately, these directions require either a large number of small Gaussians or expensive per-pixel post-processing for reconstructing fine details, which negatively impacts rendering performance. To meet the high performance demands of virtual reality (VR) systems, primitive or pixel counts therefore must be kept low, affecting visual quality. In this paper, we propose a novel hybrid approach based on foveated rendering as a promising solution that combines the strengths of both point rendering directions regarding performance sweet spots. Analyzing the compatibility with the human visual system, we find that using a low-detailed, few primitive smooth Gaussian representation for the periphery is cheap to compute and meets the perceptual demands of peripheral vision. For the fovea only, we use neural points with a convolutional neural network for the small pixel footprint, which provides sharp, detailed output within the rendering budget. This combination also allows for synergistic method accelerations with point occlusion culling and reducing the demands on the neural network. Our evaluation confirms that our approach increases sharpness and details compared to a standard VR-ready 3DGS configuration, and participants of a user study overwhelmingly preferred our method. Our system meets the necessary performance requirements for real-time VR interactions, ultimately enhancing the user's immersive experience. The project page can be found at: https://lfranke.github.io/vr_splatting

• The paper presents a hybrid foveated rendering system that integrates neural point rendering and 3D Gaussian splatting for efficient, high-fidelity VR scene rendering.
• The method achieves a steady 90Hz frame rate by differentially processing the foveal and peripheral regions to enhance sharpness and reduce artifacts.
• User studies validate the system's superiority over traditional approaches, indicating its potential for advanced VR applications in gaming, simulations, and telepresence.

Overview of VR-Splatting: Foveated Radiance Field Rendering

The paper "VR-Splatting: Foveated Radiance Field Rendering via 3D Gaussian Splatting and Neural Points" examines the integration of neural point rendering and 3D Gaussian splatting (3DGS) for achieving high-fidelity and efficient virtual reality (VR) rendering. This research addresses the challenges posed by latency and the intensive computational demands of real-time VR applications, particularly in the context of virtual teleportation and virtual tourism.

Methodological Approach

The authors propose a hybrid foveated rendering system that differentially handles the foveal and peripheral regions of the user's vision. This approach leverages the innate falloff of visual acuity to optimize processing resources while maintaining visual quality. By rendering crisp, detail-rich scenes in the foveal region using neural point rendering (TRIPS) and employing the volumetric and smooth characteristics of 3DGS for the periphery, the system fulfills the necessary frame rate requirements for VR.

Evaluation and Results

A salient aspect of this work is its balance between rendering speed and image quality. The proposed method achieves a 90Hz frame rate, essential for avoiding motion sickness in VR, while outperforming traditional VR-ready Gaussian splatting configurations (VR-GS) in terms of perceived sharpness and immersive experience. The inclusion of temporal stability and reduced artifact occurrence further underscores the practical applicability of the system.

Quantitative evaluations demonstrate that the system maintains competitive performance across several image quality metrics, such as LPIPS and PSNR, specifically in the foveal regions. The authors also conducted a comprehensive user paper, revealing a strong preference for their system over baseline VR-GS methods, thus confirming the efficacy of their approach.

Theoretical and Practical Implications

This paper contributes to the field by demonstrating the viability of hybrid rendering techniques in VR applications. The dual-method approach capitalizes on the complementary strengths of neural point and Gaussian splatting methodologies. The potential for reduced latency and improved image fidelity without a proportional increase in computational costs suggests meaningful advancements in VR rendering techniques.

Moreover, the use of foveated rendering hints at broader applications in virtual interactive environments, offering enhanced performance for a variety of sectors such as gaming, simulations, and remote applications in telepresence technologies.

Future Directions

The research opens avenues for exploring more sophisticated machine learning models or neural network architectures that could further reduce latency and improve integration between the two rendering components. As hardware evolves, particularly in eye-tracking precision and VR display technology, the methods proposed in this paper could be further refined and expanded.

In summary, this paper provides a noteworthy contribution to the field of VR rendering by effectively merging state-of-the-art novel view synthesis methods to substantially enhance user experience in VR environments.