Recent advances in novel view synthesis (NVS), particularly neural radiance fields (NeRF) and Gaussian splatting (3DGS), have demonstrated impressive results in photorealistic scene rendering. These techniques hold great potential for applications in virtual tourism and teleportation, where immersive realism is crucial. However, the high-performance demands of virtual reality (VR) systems present challenges in directly utilizing even such fast-to-render scene representations like 3DGS due to latency and computational constraints. In this paper, we propose foveated rendering as a promising solution to these obstacles. We analyze state-of-the-art NVS methods with respect to their rendering performance and compatibility with the human visual system. Our approach introduces a novel foveated rendering approach for Virtual Reality, that leverages the sharp, detailed output of neural point rendering for the foveal region, fused with a smooth rendering of 3DGS for the peripheral vision. Our evaluation confirms that perceived sharpness and detail-richness are increased by our approach compared to a standard VR-ready 3DGS configuration. Our system meets the necessary performance requirements for real-time VR interactions, ultimately enhancing the user's immersive experience. Project page: https://lfranke.github.io/vr_splatting
Linus Franke
Laura Fink
Marc Stamminger