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BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis

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We present a method for reconstructing high-quality meshes of large unbounded real-world scenes suitable for photorealistic novel view synthesis. We first optimize a hybrid neural volume-surface scene representation designed to have well-behaved level sets that correspond to surfaces in the scene. We then bake this representation into a high-quality triangle mesh, which we equip with a simple and fast view-dependent appearance model based on spherical Gaussians. Finally, we optimize this baked representation to best reproduce the captured viewpoints, resulting in a model that can leverage accelerated polygon rasterization pipelines for real-time view synthesis on commodity hardware. Our approach outperforms previous scene representations for real-time rendering in terms of accuracy, speed, and power consumption, and produces high quality meshes that enable applications such as appearance editing and physical simulation.

Lior Yariv, Peter Hedman, Christian Reiser, Dor Verbin, Pratul P. Srinivasan, Richard Szeliski, Jonathan T. Barron, Ben Mildenhall• 2023

Related benchmarks

TaskDatasetResultRank
Novel View SynthesisMipNeRF 360 Outdoor
PSNR22.47
112
Novel View SynthesisMipNeRF 360 Indoor
PSNR29.15
108
Novel View SynthesisMip-NeRF 360
PSNR26.42
102
View Synthesis and Surface ReconstructionShiny Blender
PSNR25.6
11
View SynthesisRef-NeRF real
PSNR24.43
6
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