BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis
- URL: http://arxiv.org/abs/2302.14859v2
- Date: Tue, 16 May 2023 15:01:42 GMT
- Title: BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis
- Authors: Lior Yariv, Peter Hedman, Christian Reiser, Dor Verbin, Pratul P.
Srinivasan, Richard Szeliski, Jonathan T. Barron, Ben Mildenhall
- Abstract summary: We present a method for reconstructing high-quality meshes of large 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.
- Score: 42.93055827628597
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
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