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Virtual Reality (VR) is becoming ubiquitous with the rise of consumerdisplays and commercial VR platforms. Such displays require low latency andhigh quality rendering of synthetic imagery with reduced compute overheads.Recent advances in neural rendering showed promise of unlocking newpossibilities in 3D computer graphics via image-based representations ofvirtual or physical environments. Specifically, the neural radiance fields(NeRF) demonstrated that photo-realistic quality and continuous view changes of3D scenes can be achieved without loss of view-dependent effects. While NeRFcan significantly benefit rendering for VR applications, it faces uniquechallenges posed by high field-of-view, high resolution, andstereoscopic/egocentric viewing, typically causing low quality and high latencyof the rendered images. In VR, this not only harms the interaction experiencebut may also cause sickness. To tackle these problems towardsix-degrees-of-freedom, egocentric, and stereo NeRF in VR, we present the firstgaze-contingent 3D neural representation and view synthesis method. Weincorporate the human psychophysics of visual- and stereo-acuity into anegocentric neural representation of 3D scenery. We then jointly optimize thelatency/performance and visual quality while mutually bridging human perceptionand neural scene synthesis to achieve perceptually high-quality immersiveinteraction. We conducted both objective analysis and subjective studies toevaluate the effectiveness of our approach. We find that our methodsignificantly reduces latency (up to 99% time reduction compared with NeRF)without loss of high-fidelity rendering (perceptually identical tofull-resolution ground truth). The presented approach may serve as the firststep toward future VR/AR systems that capture, teleport, and visualize remoteenvironments in real-time.

FoV-NeRF: Foveated Neural Radiance Fields for Virtual Reality