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Extracting Triangular 3D Models, Materials, and Lighting From Images
[article]
2022
arXiv
pre-print
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
arXiv:2111.12503v4
fatcat:zvcxx7txtnb3raqcdczwmu3n5i