A Composite BRDF Model for Hazy Gloss

We introduce a bidirectional reflectance distribution function (BRDF) model for the rendering of materials that exhibit hazy reflections, whereby the specular reflections appear to be flanked by a surrounding halo. The focus of this work is on artistic control and ease of implementation for real‐time and off‐line rendering. We propose relying on a composite material based on a pair of arbitrary BRDF models; however, instead of controlling their physical parameters, we expose perceptual parameters inspired by visual experiments [ VBF17 ]. Our main contribution then consists in a mapping from perceptual to physical parameters that ensures the resulting composite BRDF is valid in terms of reciprocity, positivity and energy conservation. The immediate benefit of our approach is to provide direct artistic control over both the intensity and extent of the haze effect, which is not only necessary for editing purposes, but also essential to vary haziness spatially over an object surface. Our solution is also simple to implement as it requires no new importance sampling strategy and relies on existing BRDF models. Such a simplicity is key to approximating the method for the editing of hazy gloss in real‐time and for compositing.     

On‐Site Example‐Based Material Appearance Acquisition

We present a novel example‐based material appearance modeling method suitable for rapid digital content creation. Our method only requires a single HDR photograph of a homogeneous isotropic dielectric exemplar object under known natural illumination. While conventional methods for appearance modeling require prior knowledge on the object shape, our method does not, nor does it recover the shape explicitly, greatly simplifying on‐site appearance acquisition to a lightweight photography process suited for non‐expert users. As our central contribution, we propose a shape‐agnostic BRDF estimation procedure based on binary RGB profile matching. We also model the appearance of materials exhibiting a regular or stationary texture‐like appearance, by synthesizing appropriate mesostructure from the same input HDR photograph and a mesostructure exemplar with (roughly) similar features. We believe our lightweight method for on‐site shape‐agnostic appearance acquisition presents a suitable alternative for a variety of applications that require plausible “rapid‐appearance‐modeling”.     

A Low‐Dimensional Function Space for Efficient Spectral Upsampling

We present a versatile technique to convert textures with tristimulus colors into the spectral domain, allowing such content to be used in modern rendering systems. Our method is based on the observation that suitable reflectance spectra can be represented using a low‐dimensional parametric model that is intrinsically smooth and energy‐conserving, which leads to significant simplifications compared to prior work. The resulting spectral textures are compact and efficient: storage requirements are identical to standard RGB textures, and as few as six floating point instructions are required to evaluate them at any wavelength. Our model is the first spectral upsampling method to achieve zero error on the full sRGB gamut. The technique also supports large‐gamut color spaces, and can be vectorized effectively for use in rendering systems that handle many wavelengths at once.     

Real‐time Indirect Illumination of Emissive Inhomogeneous Volumes using Layered Polygonal Area Lights

Indirect illumination involving with visually rich participating media such as turbulent smoke and loud explosions contributes significantly to the appearances of other objects in a rendering scene. However, previous real‐time techniques have focused only on the appearances of the media directly visible from the viewer. Specifically, appearances that can be indirectly seen over reflective surfaces have not attracted much attention. In this paper, we present a real‐time rendering technique for such indirect views that involves the participating media. To achieve real‐time performance for computing indirect views, we leverage layered polygonal area lights (LPALs) that can be obtained by slicing the media into multiple flat layers. Using this representation, radiance entering each surface point from each slice of the volume is analytically evaluated to achieve instant calculation. The analytic solution can be derived for standard bidirectional reflectance distribution functions (BRDFs) based on the microfacet theory. Accordingly, our method is sufficiently robust to work on surfaces with arbitrary shapes and roughness values. In addition, we propose a quadrature method for more accurate rendering of scenes with dense volumes, and a transformation of the domain of volumes to simplify the calculation and implementation of the proposed method. By taking advantage of these computation techniques, the proposed method achieves real‐time rendering of indirect illumination for emissive volumes.     

Attribute‐preserving gamut mapping of measured BRDFs

Reproducing the appearance of real‐world materials using current printing technology is problematic. The reduced number of inks available define the printer's limited gamut, creating distortions in the printed appearance that are hard to control. Gamut mapping refers to the process of bringing an out‐of‐gamut material appearance into the printer's gamut, while minimizing such distortions as much as possible. We present a novel two‐step gamut mapping algorithm that allows users to specify which perceptual attribute of the original material they want to preserve (such as brightness, or roughness). In the first step, we work in the low‐dimensional intuitive appearance space recently proposed by Serrano et al. [ SGM*16 ], and adjust achromatic reflectance via an objective function that strives to preserve certain attributes. From such intermediate representation, we then perform an image‐based optimization including color information, to bring the BRDF into gamut. We show, both objectively and through a user study, how our method yields superior results compared to the state of the art, with the additional advantage that the user can specify which visual attributes need to be preserved. Moreover, we show how this approach can also be used for attribute‐preserving material editing.     

Glint Rendering based on a Multiple‐Scattering Patch BRDF

Rendering materials such as metallic paints, scratched metals and rough plastics requires glint integrators that can capture all micro‐specular highlights falling into a pixel footprint, faithfully replicating surface appearance. Specular normal maps can be used to represent a wide range of arbitrary micro‐structures. The use of normal maps comes with important drawbacks though: the appearance is dark overall due to back‐facing normals and importance sampling is suboptimal, especially when the micro‐surface is very rough. We propose a new glint integrator relying on a multiple‐scattering patch‐based BRDF addressing these issues. To do so, our method uses a modified version of microfacet‐based normal mapping [SHHD17] designed for glint rendering, leveraging symmetric microfacets. To model multiple‐scattering, we re‐introduce the lost energy caused by a perfectly specular, single‐scattering formulation instead of using expensive random walks. This reflectance model is the basis of our patch‐based BRDF, enabling robust sampling and artifact‐free rendering with a natural appearance. Additional calculation costs amount to about 40% in the worst cases compared to previous methods [YHMR16, CCM18].     

Learned Fitting of Spatially Varying BRDFs

The use of spatially varying reflectance models (SVBRDF) is the state of the art in physically based rendering and the ultimate goal is to acquire them from real world samples. Recently several promising deep learning approaches have emerged that create such models from a few uncalibrated photos, after being trained on synthetic SVBRDF datasets. While the achieved results are already very impressive, the reconstruction accuracy that is achieved by these approaches is still far from that of specialized devices. On the other hand, fitting SVBRDF parameter maps to the gibabytes of calibrated HDR images per material acquired by state of the art high quality material scanners takes on the order of several hours for realistic spatial resolutions. In this paper, we present a first deep learning approach that is capable of producing SVBRDF parameter maps more than two orders of magnitude faster than state of the art approaches, while still providing results of equal quality and generalizing to new materials unseen during the training. This is made possible by training our network on a large‐scale database of material scans that we have gathered with a commercially available SVBRDF scanner. In particular, we train a convolutional neural network to map calibrated input images to the 13 parameter maps of an anisotropic Ward BRDF, modified to account for Fresnel reflections, and evaluate the results by comparing the measured images against re‐renderings from our SVBRDF predictions. The novel approach is extensively validated on real world data taken from our material database, which we make publicly available under https://cg.cs.uni‐bonn.de/svbrdfs/ .     

Global Texture Mapping for Dynamic Objects

We propose a novel framework to generate a global texture atlas for a deforming geometry. Our approach distinguishes from prior arts in two aspects. First, instead of generating a texture map for each timestamp to color a dynamic scene, our framework reconstructs a global texture atlas that can be consistently mapped to a deforming object. Second, our approach is based on a single RGB‐D camera, without the need of a multiple‐camera setup surrounding a scene. In our framework, the input is a 3D template model with an RGB‐D image sequence, and geometric warping fields are found using a state‐of‐the‐art non‐rigid registration method [GXW*15] to align the template mesh to noisy and incomplete input depth images. With these warping fields, our multi‐scale approach for texture coordinate optimization generates a sharp and clear texture atlas that is consistent with multiple color observations over time. Our approach is accelerated by graphical hardware and provides a handy configuration to capture a dynamic geometry along with a clean texture atlas. We demonstrate our approach with practical scenarios, particularly human performance capture. We also show that our approach is resilient on misalignment issues caused by imperfect estimation of warping fields and inaccurate camera parameters.     

Multi‐Pose Interactive Linkage Design

We introduce an interactive tool for novice users to design mechanical objects made of 2.5D linkages. Users simply draw the shape of the object and a few key poses of its multiple moving parts. Our approach automatically generates a one‐degree‐of freedom linkage that connects the fixed and moving parts, such that the moving parts traverse all input poses in order without any collision with the fixed and other moving parts. In addition, our approach avoids common linkage defects and favors compact linkages and smooth motion trajectories. Finally, our system automatically generates the 3D geometry of the object and its links, allowing the rapid creation of a physical mockup of the designed object.     

Procedural Modeling of a Building from a Single Image

Creating a virtual city is demanded for computer games, movies, and urban planning, but it takes a lot of time to create numerous 3D building models. Procedural modeling has become popular in recent years to overcome this issue, but creating a grammar to get a desired output is difficult and time consuming even for expert users. In this paper, we present an interactive tool that allows users to automatically generate such a grammar from a single image of a building. The user selects a photograph and highlights the silhouette of the target building as input to our method. Our pipeline automatically generates the building components, from large‐scale building mass to fine‐scale windows and doors geometry. Each stage of our pipeline combines convolutional neural networks (CNNs) and optimization to select and parameterize procedural grammars that reproduce the building elements of the picture. In the first stage, our method jointly estimates camera parameters and building mass shape. Once known, the building mass enables the rectification of the façades, which are given as input to the second stage that recovers the façade layout. This layout allows us to extract individual windows and doors that are subsequently fed to the last stage of the pipeline that selects procedural grammars for windows and doors. Finally, the grammars are combined to generate a complete procedural building as output. We devise a common methodology to make each stage of this pipeline tractable. This methodology consists in simplifying the input image to match the visual appearance of synthetic training data, and in using optimization to refine the parameters estimated by CNNs. We used our method to generate a variety of procedural models of buildings from existing photographs.     

Real‐time Image‐based Lighting of Microfacet BRDFs with Varying Iridescence

Iridescence is a natural phenomenon that is perceived as gradual color changes, depending on the view and illumination direction. Prominent examples are the colors seen in oil films and soap bubbles. Unfortunately, iridescent effects are particularly difficult to recreate in real‐time computer graphics. We present a high‐quality real‐time method for rendering iridescent effects under image‐based lighting. Previous methods model dielectric thin‐films of varying thickness on top of an arbitrary micro‐facet model with a conducting or dielectric base material, and evaluate the resulting reflectance term, responsible for the iridescent effects, only for a single direction when using real‐time image‐based lighting. This leads to bright halos at grazing angles and over‐saturated colors on rough surfaces, which causes an unnatural appearance that is not observed in ground truth data. We address this problem by taking the distribution of light directions, given by the environment map and surface roughness, into account when evaluating the reflectance term. In particular, our approach prefilters the first and second moments of the light direction, which are used to evaluate a filtered version of the reflectance term. We show that the visual quality of our approach is superior to the ones previously achieved, while having only a small negative impact on performance.     

Sequences with Low‐Discrepancy Blue‐Noise 2‐D Projections

Distributions of samples play a very important role in rendering, affecting variance, bias and aliasing in Monte‐Carlo and Quasi‐Monte Carlo evaluation of the rendering equation. In this paper, we propose an original sampler which inherits many important features of classical low‐discrepancy sequences (LDS): a high degree of uniformity of the achieved distribution of samples, computational efficiency and progressive sampling capability. At the same time, we purposely tailor our sampler in order to improve its spectral characteristics, which in turn play a crucial role in variance reduction, anti‐aliasing and improving visual appearance of rendering. Our sampler can efficiently generate sequences of multidimensional points, whose power spectra approach so‐called Blue‐Noise (BN) spectral property while preserving low discrepancy (LD) in certain 2‐D projections. In our tile‐based approach, we perform permutations on subsets of the original Sobol LDS. In a large space of all possible permutations, we select those which better approach the target BN property, using pair‐correlation statistics. We pre‐calculate such “good” permutations for each possible Sobol pattern, and store them in a lookup table efficiently accessible in runtime. We provide a complete and rigorous proof that such permutations preserve dyadic partitioning and thus the LDS properties of the point set in 2‐D projections. Our construction is computationally efficient, has a relatively low memory footprint and supports adaptive sampling. We validate our method by performing spectral/discrepancy/aliasing analysis of the achieved distributions, and provide variance analysis for several target integrands of theoretical and practical interest.     

Bi‐Layer textures: a Model for Synthesis and Deformation of Composite Textures

We propose a bi‐layer representation for textures which is suitable for on‐the‐fly synthesis of unbounded textures from an input exemplar. The goal is to improve the variety of outputs while preserving plausible small‐scale details. The insight is that many natural textures can be decomposed into a series of fine scale Gaussian patterns which have to be faithfully reproduced, and some non‐homogeneous, larger scale structure which can be deformed to add variety. Our key contribution is a novel, bi‐layer representation for such textures. It includes a model for spatially‐varying Gaussian noise, together with a mechanism enabling synchronization with a structure layer. We propose an automatic method to instantiate our bi‐layer model from an input exemplar. At the synthesis stage, the two layers are generated independently, synchronized and added, preserving the consistency of details even when the structure layer has been deformed to increase variety. We show on a variety of complex, real textures, that our method reduces repetition artifacts while preserving a coherent appearance.     

Distortion‐Free Displacement Mapping

Displacement mapping is routinely used to add geometric details in a fast and easy‐to‐control way, both in offline rendering as well as recently in interactive applications such as games. However, it went largely unnoticed (with the exception of McGuire and Whitson [MW08]) that, when applying displacement mapping to a surface with a low‐distortion parametrization, this parametrization is distorted as the geometry was changed by the displacement mapping. Typical resulting artifacts are “rubber band”‐like distortion patterns in areas of strong displacement change where a small isotropic area in texture space is mapped to a large anisotropic area in world space. We describe a fast, fully GPU‐based two‐step procedure to resolve this problem. First, a correction deformation is computed from the displacement map. Second, two variants to apply this correction when computing displacement mapping are proposed. The first variant is backward‐compatible and can resolve the artifact in any rendering pipeline without modifying it and without requiring additional computation at render time, but only works for bijective parametrizations. The second variant works for more general parametrizations, but requires to modify the rendering code and incurs a very small computational overhead.