NVlabs/intrinsic3d
A 2017 ICCV paper implementing joint optimization of 3D geometry, surface albedo, camera poses, and scene lighting from RGB-D sensor data.

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Intrinsic3D recovers high-quality 3D reconstructions from low-cost RGB-D sensors by simultaneously optimizing reconstructed geometry, surface albedos, camera poses, and spatially-varying lighting modeled via spherical harmonics. The method uses SDF-based surface representation and classical optimization rather than deep learning. Published by NVIDIA Research and TU Munich.