Extracting Triangular 3D Models, Materials, and Lighting From Images
- URL: http://arxiv.org/abs/2111.12503v5
- Date: Tue, 11 Apr 2023 07:05:24 GMT
- Title: Extracting Triangular 3D Models, Materials, and Lighting From Images
- Authors: Jacob Munkberg, Jon Hasselgren, Tianchang Shen, Jun Gao, Wenzheng
Chen, Alex Evans, Thomas M\"uller, Sanja Fidler
- Abstract summary: We present an efficient method for joint optimization of materials and lighting from multi-view image observations.
We leverage meshes with spatially-varying materials and environment that can be deployed in any traditional graphics engine.
- Score: 59.33666140713829
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We present an efficient method for joint optimization of topology, materials
and lighting from multi-view image observations. Unlike recent multi-view
reconstruction approaches, which typically produce entangled 3D representations
encoded in neural networks, we output triangle meshes with spatially-varying
materials and environment lighting that can be deployed in any traditional
graphics engine unmodified. We leverage recent work in differentiable
rendering, coordinate-based networks to compactly represent volumetric
texturing, alongside differentiable marching tetrahedrons to enable
gradient-based optimization directly on the surface mesh. Finally, we introduce
a differentiable formulation of the split sum approximation of environment
lighting to efficiently recover all-frequency lighting. Experiments show our
extracted models used in advanced scene editing, material decomposition, and
high quality view interpolation, all running at interactive rates in
triangle-based renderers (rasterizers and path tracers). Project website:
https://nvlabs.github.io/nvdiffrec/ .
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