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Found 4 papers, 1 papers with code
NeISF++: Neural Incident Stokes Field for Polarized Inverse Rendering of Conductors and Dielectrics
As for the strong specular reflection problem, we propose a novel geometry initialization method using DoLP images.
Joint Reconstruction and Spatial Super-Resolution of Hyper-Spectral CTIS Images via Multi-Scale Refinement
Furthermore, we introduce HSIRS, the largest dataset of its kind for joint spectral image reconstruction and semantic segmentation of food items with high quality manually annotated segmentation maps and we showcase how hyper-spectral data allows to efficiently tackle this task.
NeISF: Neural Incident Stokes Field for Geometry and Material Estimation
To address this problem, we propose Neural Incident Stokes Fields (NeISF), a multi-view inverse rendering framework that reduces ambiguities using polarization cues.
Heterogeneous Light Fields
In contrast to traditional binocular or multi-view stereo approaches, the adequately sampled space of observations in light-field imaging allows, to obtain dense and high quality depth maps.
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