Acquiring bidirectional reflectance distribution functions (BRDFs) is essential for simulating light transport and analytically modeling material properties.
Over the past two decades, numerous intensity-only BRDF datasets in the visible spectrum have been introduced, primarily for RGB image rendering applications.
However, in scientific and engineering domains, there remains an unmet need to model light transport with polarization-a fundamental wave property of light-across hyperspectral bands.
To address this gap, we present the first hyperspectral-polarimetric BRDF (hpBRDF) dataset of real-world materials, spanning wavelengths from 414 to 950nm and densely sampled at 68 spectral bands.
This dataset covers both the visible and near-infrared (NIR) spectra, enabling detailed material analysis and light reflection simulations that incorporate polarization at each narrow spectral band.
We develop an hpBRDF acquisition system that captures high-dimensional hpBRDFs within a practical acquisition time.
Using this system, we demonstrate hyperspectral-polarimetric rendering using the acquired hpBRDFs.
To provide insights on hpBRDF, we analyze the hpBRDFs with respect to their dependencies on wavelength, polarization state, material type, and illumination/viewing geometry.
Also, we propose compact representations through principal component analysis and implicit neural hpBRDF modeling.