Fresnel Microfacet BRDF: Unification of Polari-Radiometric Surface-Body Reflection
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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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 5 of its 41 references that are in the map. First posted on arXiv 8 Dec 2022.
Builds on
5 of 41 references.
References · 5
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2019Depth from a polarisation + RGB stereo paircited by 29
- 2020Invertible Neural BRDF for Object Inverse Renderingcited by 17
- 2022Perspective Phase Angle Model for Polarimetric 3D Reconstructioncited by 11
- 2022Sparse Ellipsometry: Portable Acquisition of Polarimetric SVBRDF and Shape with Unstructured Flash Photographycited by 7
Built on by
Citing papers per year: 2023: 1; 2024: 2; 2025: 3.
6 papers.
- 2024PISR: Polarimetric Neural Implicit Surface Reconstruction for Textureless and Specular Objectscited by 15
- 2024NeISF++: Neural Incident Stokes Field for Polarized Inverse Rendering of Conductors and Dielectricscited by 9
- 2023SPIDeRS: Structured Polarization for Invisible Depth and Reflectance Sensingcited by 6
- 2025PolarAnything: Diffusion-based Polarimetric Image Synthesiscited by 5
- 2025On Neural BRDFs: A Thorough Comparison of State-of-the-Art Approachescited by 2
- 2025Spatial Polarization Multiplexing: Single-Shot Invisible Shape and Reflectance Recoverycited by 0
- 2025PolarAnything: Diffusion-based Polarimetric Image Synthesis23 Jul 2025
- 2025Spatial Polarization Multiplexing: Single-Shot Invisible Shape and Reflectance Recovery17 Apr 2025
- 2025On Neural BRDFs: A Thorough Comparison of State-of-the-Art Approaches21 Feb 2025
- 2024NeISF++: Neural Incident Stokes Field for Polarized Inverse Rendering of Conductors and Dielectrics15 Nov 2024
- 2024PISR: Polarimetric Neural Implicit Surface Reconstruction for Textureless and Specular Objects22 Sep 2024
- 2023SPIDeRS: Structured Polarization for Invisible Depth and Reflectance Sensing7 Dec 2023