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We present a system for acquiring, processing, and rendering panoramic light field still photography for display in Virtual Reality (VR). We acquire spherical light field datasets with two novel light field camera rigs designed for portable and efficient light field acquisition. We introduce a novel real-time light field reconstruction algorithm that uses a per-view geometry and a disk-based blending field. We also demonstrate how to use a light field prefiltering operation to project from a high-quality offline reconstruction model into our real-time model while suppressing artifacts. We introduce a practical approach for compressing light fields by modifying the VP9 video codec to provide high quality compression with real-time, random access decompression. We combine these components into a complete light field system offering convenient acquisition, compact file size, and high-quality rendering while generating stereo views at 90Hz on commodity VR hardware. Using our system, we built a freely available light field experience application called Welcome to Light Fields featuring a library of panoramic light field stills for consumer VR which has been downloaded over 15,000 times., Comment: 15 pages, 14 figures, 2 tables, accepted by SIGGRAPH Asia 2018, low-resolution version

Efficiently rendering direct lighting from millions of dynamic light sources using Monte Carlo integration remains a challenging problem, even for off-line rendering systems. We introduce a new algorithm---ReSTIR---that renders such lighting interactively, at high quality, and without needing to maintain complex data structures. We repeatedly resample a set of candidate light samples and apply further spatial and temporal resampling to leverage information from relevant nearby samples. We derive an unbiased Monte Carlo estimator for this approach, and show that it achieves equal-error 6×-60× faster than state-of-the-art methods. A biased estimator reduces noise further and is 35×-65× faster, at the cost of some energy loss. We implemented our approach on the GPU, rendering complex scenes containing up to 3.4 million dynamic, emissive triangles in under 50 ms per frame while tracing at most 8 rays per pixel.

We present a new algorithm for image-based simplification of complex scenes for virtual reality (VR). The algorithm transforms geometrically-detailed environments into a layered quad tile representation that is optimized for a specified viewing region and is renderable on low-power mobile-class VR devices. A novel constrained optimization formulation ensures that the scene can be rendered within a predetermined compute budget, with limits on both primitive count and fill rate. Furthermore, we introduce a new method for texturing from point samples of the original scene geometry that generates high-quality silhouettes without the drawbacks of traditional point splatting. The resulting representation achieves a visual fidelity that was previously impossible on mobile graphics hardware; our algorithm can typically generate a high-quality representation of visually-rich scenes with billions of triangles using just 72k triangles and a single high-resolution texture map (with generally only about 50% more texels than a stereo panorama). The effectiveness of the approach is demonstrated with a set of challenging test cases.