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Found 4 papers, 2 papers with code
Towards Scalable Multi-View Reconstruction of Geometry and Materials
In this paper, we propose a novel method for joint recovery of camera pose, object geometry and spatially-varying Bidirectional Reflectance Distribution Function (svBRDF) of 3D scenes that exceed object-scale and hence cannot be captured with stationary light stages.
SMD-Nets: Stereo Mixture Density Networks
Despite stereo matching accuracy has greatly improved by deep learning in the last few years, recovering sharp boundaries and high-resolution outputs efficiently remains challenging.
On Joint Estimation of Pose, Geometry and svBRDF From a Handheld Scanner
We propose a novel formulation for joint recovery of camera pose, object geometry and spatially-varying BRDF.
RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials
RayNet integrates a CNN that learns view-invariant feature representations with an MRF that explicitly encodes the physics of perspective projection and occlusion.
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