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Person# Tizian Lucien Zeltner

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Rendering (computer graphics)

Rendering or image synthesis is the process of generating a photorealistic or non-photorealistic image from a 2D or 3D model by means of a computer program. The resulting image is referred to as t

Diffuse reflection

Diffuse reflection is the reflection of light or other waves or particles from a surface such that a ray incident on the surface is scattered at many angles rather than at just one angle as in the ca

Metropolis light transport

Metropolis light transport (MLT) is a global illumination application of a variant of the Monte Carlo method called the Metropolis–Hastings algorithm to the rendering equation for generating images fr

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Wenzel Alban Jakob, Xin Tong, Tizian Lucien Zeltner

Realistic modeling of the bidirectional reflectance distribution function (BRDF) of scene objects is a vital prerequisite for any type of physically based rendering. In the last decades, the availability of databases containing real-world material measurements has fueled considerable innovation in the development of such models. However, previous work in this area was mainly focused on increasing the visual realism of images, and hence ignored the effect of scattering on the polarization state of light, which is normally imperceptible to the human eye. Existing databases thus only capture scattered flux, or polarimetric BRDF datasets are too directionally sparse (e.g., in-plane) to be usable for simulation. While subtle to human observers, polarization is easily perceived by any optical sensor (e.g., using polarizing filters), providing a wealth of additional information about shape and material properties of the object under observation. Given the increasing application of rendering in the solution of inverse problems via analysis-by-synthesis and differentiation, the ability to realistically model polarized radiative transport is thus highly desirable. Polarization depends on the wavelength of the spectrum, and thus we provide the first polarimetric BRDF (pBRDF) dataset that captures the polarimetric properties of real-world materials over the full angular domain, and at multiple wavelengths. Acquisition of such reflectance data is challenging due to the extremely large space of angular, spectral, and polarimetric configurations that must be observed, and we propose a scheme combining image-based acquisition with spectroscopic ellipsometry to perform measurements in a realistic amount of time. This process yields raw Mueller matrices, which we subsequently transform into Rusinkiewicz-parameterized pBRDFs that can be used for rendering. Our dataset provides 25 isotropic pBRDFs spanning a wide range of appearances: diffuse/specular, metallic/dielectric, rough/smooth, and different color albedos, captured in five wavelength ranges covering the visible spectrum. We demonstrate usage of our data-driven pBRDF model in a physically based renderer that accounts for polarized interreflection, and we investigate the relationship of polarization and material appearance, providing insights into the behavior of characteristic real-world pBRDFs.

Wenzel Alban Jakob, Sébastien Nicolas Speierer, Tizian Lucien Zeltner

Physically based differentiable rendering algorithms propagate derivatives through realistic light transport simulations and have applications in diverse areas including inverse reconstruction and machine learning. Recent progress has led to unbiased methods that can simultaneously compute derivatives with respect to millions of parameters. At the same time, elementary properties of these methods remain poorly understood. Current algorithms for differentiable rendering are constructed by mechanically differentiating a given primal algorithm. While convenient, such an approach is simplistic because it leaves no room for improvement. Differentiation produces major changes in the integrals that occur throughout the rendering process, which indicates that the primal and differential algorithms should be decoupled so that the latter can suitably adapt. This leads to a large space of possibilities: consider that even the most basic Monte Carlo path tracer already involves several design choices concerning the techniques for sampling materials and emitters, and their combination, e.g. via multiple importance sampling (MIS). Differentiation causes a veritable explosion of this decision tree: should we differentiate only the estimator, or also the sampling technique? Should MIS be applied before or after differentiation? Are specialized derivative sampling strategies of any use? How should visibility-related discontinuities be handled when millions of parameters are differentiated simultaneously? In this paper, we provide a taxonomy and analysis of different estimators for differential light transport to provide intuition about these and related questions.

Physically based rendering is a process for photorealistic digital image synthesis and one of the core problems in computer graphics. It involves simulating the light transport, i.e. the emission, propagation, and scattering of light through a virtual scene that is defined by a detailed description of object geometry and appearance. Research over the last decades has led to sophisticated rendering techniques and recently, the inversion of this process, i.e. recovering scene parameters from image observations, has also received significant attention. In this thesis, we investigate methods in both physically based forward and inverse rendering that exploit light path gradients.The first part is concerned with scattering from specular surfaces, which produces complex optical effects that are frequently encountered in realistic scenes: intricate caustics due to focused reflection, multiple refractions, and high-frequency glints from specular microstructure. Yet, despite their importance and considerable research to this end, sampling of light paths that cause these effects remains a formidable challenge of forward rendering.We propose a surprisingly simple and general path sampling strategy that targets the examples above. Valid light path configurations need to fulfill the physical laws of reflection and refraction, and we find these using a numerical root-finding process that is driven by geometric light path gradients. In contrast to prior work, our method supports high-frequency normal- or displacement-mapped geometry, samples specular-diffuse-specular (SDS) paths, and is compatible with standard Monte Carlo methods including unidirectional path tracing. We demonstrate our method on a range of challenging scenes and evaluate it against state-of-the-art methods for rendering caustics and glints.In the second part, we consider differentiable rendering algorithms. These propagate derivatives through the full light transport simulation to solve inverse rendering problems via gradient-based optimization. Recent progress has led to methods that can simultaneously compute derivatives with respect to millions of scene parameters. At the same time, elementary properties of these methods remain poorly understood.Current algorithms for differentiable rendering are constructed by mechanically differentiating a given primal algorithm. As differentiation fundamentally changes the underlying problem, this is often suboptimal and instead, primal and differential algorithms should be decoupled so that the latter can suitably adapt. This is surprisingly complex. Even the most basic Monte Carlo path tracer already involves several design choices concerning the techniques for sampling materials and emitters, and their combination, e.g. via multiple importance sampling (MIS). Differentiation causes a veritable explosion of this decision tree: should we differentiate only the estimator, or also the sampling technique? Should MIS be applied before or after differentiation? Are specialized derivative sampling strategies of any use? How should visibility-related discontinuities be handled when millions of parameters are differentiated simultaneously? We provide a taxonomy and analysis of different estimators for differential light transport to provide intuition about these and related questions.