# Fresnel Microfacet BRDF: Unification of Polari-Radiometric Surface-Body Reflection

arXiv: https://arxiv.org/abs/2212.04483 · HTML: https://mlsanity.com/paper/2212.04483/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 41 references that are in the map.
- First posted on arXiv 8 Dec 2022.

## Builds on (most cited first, 5 of 5)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Depth from a polarisation + RGB stereo pair](https://mlsanity.com/paper/1903.12061/) (2019)
- [Invertible Neural BRDF for Object Inverse Rendering](https://mlsanity.com/paper/2008.04030/) (2020)
- [Perspective Phase Angle Model for Polarimetric 3D Reconstruction](https://mlsanity.com/paper/2207.09629/) (2022)
- [Sparse Ellipsometry: Portable Acquisition of Polarimetric SVBRDF and Shape with Unstructured Flash Photography](https://mlsanity.com/paper/2207.04236/) (2022)

## Built on by (most cited first, 6 of 6)

- [PISR: Polarimetric Neural Implicit Surface Reconstruction for Textureless and Specular Objects](https://mlsanity.com/paper/2409.14331/) (2024)
- [NeISF++: Neural Incident Stokes Field for Polarized Inverse Rendering of Conductors and Dielectrics](https://mlsanity.com/paper/2411.10189/) (2024)
- [SPIDeRS: Structured Polarization for Invisible Depth and Reflectance Sensing](https://mlsanity.com/paper/2312.04553/) (2023)
- [PolarAnything: Diffusion-based Polarimetric Image Synthesis](https://mlsanity.com/paper/2507.17268/) (2025)
- [On Neural BRDFs: A Thorough Comparison of State-of-the-Art Approaches](https://mlsanity.com/paper/2502.15480/) (2025)
- [Spatial Polarization Multiplexing: Single-Shot Invisible Shape and Reflectance Recovery](https://mlsanity.com/paper/2504.13177/) (2025)

## Abstract (arXiv)

Computer vision applications have heavily relied on the linear combination of Lambertian diffuse and microfacet specular reflection models for representing reflected radiance, which turns out to be physically incompatible and limited in applicability. In this paper, we derive a novel analytical reflectance model, which we refer to as Fresnel Microfacet BRDF model, that is physically accurate and generalizes to various real-world surfaces. Our key idea is to model the Fresnel reflection and transmission of the surface microgeometry with a collection of oriented mirror facets, both for body and surface reflections. We carefully derive the Fresnel reflection and transmission for each microfacet as well as the light transport between them in the subsurface. This physically-grounded modeling also allows us to express the polarimetric behavior of reflected light in addition to its radiometric behavior. That is, FMBRDF unifies not only body and surface reflections but also light reflection in radiometry and polarization and represents them in a single model. Experimental results demonstrate its effectiveness in accuracy, expressive power, and image-based estimation.