Browsing by Author "Marschner, Steve"

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Brush Stroke Synthesis with a Generative Adversarial Network Driven by Physically Based Simulation
    (ACM, 2018) Wu, Rundong; Chen, Zhili; Wang, Zhaowen; Yang, Jimei; Marschner, Steve; Aydın, Tunç and Sýkora, Daniel
    We introduce a novel approach that uses a generative adversarial network (GAN) to synthesize realistic oil painting brush strokes, where the network is trained with data generated by a high-fidelity simulator. Among approaches to digitally synthesizing natural media painting strokes, methods using physically based simulation by far produce the most realistic visual results and allow the most intuitive control of stroke variations. However, accurate physics simulations are known to be computationally expensive and often cannot meet the performance requirements of painting applications. A few existing simulation-based methods have managed to reach real-time performance at the cost of lower visual quality resulting from simplified models or lower resolution. In our work, we propose to replace the expensive fluid simulation with a neural network generator. The network takes the existing canvas and new brush trajectory information as input and produces the height and color of the paint surface as output. We build a large painting sample training dataset by feeding random strokes from artists' recordings into a high quality offline simulator. The network is able to produce visual quality comparable to the offline simulator with better performance than the existing real-time oil painting simulator. Finally, we implement a real-time painting system using the trained network with stroke splitting and patch blending and show artworks created with the system by artists. Our neural network approach opens up new opportunities for real-time applications of sophisticated and expensive physically based simulation.
  • Thumbnail Image
    Item
    Gaussian Product Sampling for Rendering Layered Materials
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Xia, Mengqi (Mandy); Walter, Bruce; Hery, Christophe; Marschner, Steve; Benes, Bedrich and Hauser, Helwig
    To increase diversity and realism, surface bidirectional scattering distribution functions (BSDFs) are often modelled as consisting of multiple layers, but accurately evaluating layered BSDFs while accounting for all light transport paths is a challenging problem. Recently, Guo . [GHZ18] proposed an accurate and general position‐free Monte Carlo method, but this method introduces variance that leads to longer render time compared to non‐stochastic layered models. We improve the previous work by presenting two new sampling strategies, and . Our new methods better take advantage of the layered structure and reduce variance compared to the conventional approach of sequentially sampling one BSDF at a time. Our strategy importance samples the product of two BSDFs from a pair of adjacent layers. We further generalize this to , which importance samples the product of a chain of three or more BSDFs. In order to compute these products, we developed a new approximate Gaussian representation of individual layer BSDFs. This representation incorporates spatially varying material properties as parameters so that our techniques can support an arbitrary number of textured layers. Compared to previous Monte Carlo layering approaches, our results demonstrate substantial variance reduction in rendering isotropic layered surfaces.
  • Thumbnail Image
    Item
    Iridescent Water Droplets Beyond Mie Scattering
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Xia, Mengqi (Mandy); Walter, Bruce; Marschner, Steve; Ritschel, Tobias; Weidlich, Andrea
    Looking at a cup of hot tea, an observer can see color patterns and granular textures both on the water surface and in the steam. Motivated by this example, we model the appearance of iridescent water droplets. Mie scattering describes the scattering of light waves by individual spherical particles and is the building block for both effects, but we show that other mechanisms must also be considered in order to faithfully reproduce the appearance. Iridescence on the water surface is caused by droplets levitating above the surface, and interference between light scattered by drops and reflected by the water surface, known as Quetelet scattering, is essential to producing the color. We propose a model, new to computer graphics, for rendering this phenomenon, which we validate against photographs. For iridescent steam, we show that variation in droplet size is essential to the characteristic color patterns. We build a droplet growth model and apply it as a post-processing step to an existing computer graphics fluid simulation to compute collections of particles for rendering. We significantly accelerate the rendering of sparse particles with motion blur by intersecting rays with particle trajectories, blending contributions along viewing rays. Our model reproduces the distinctive color patterns correlated with the steam flow. For both effects, we instantiate individual droplets and render them explicitly, since the granularity of droplets is readily observed in reality, and demonstrate that Mie scattering alone cannot reproduce the visual appearance.
  • Thumbnail Image
    Item
    A Taxonomy of Bidirectional Scattering Distribution Function Lobes for Rendering Engineers
    (The Eurographics Association, 2020) McGuire, Morgan; Dorsey, Julie; Haines, Eric; Hughes, John F.; Marschner, Steve; Pharr, Matt; Shirley, Peter; Klein, Reinhard and Rushmeier, Holly
    We propose a taxonomy and terminology for rendering engineers to use in describing the main categories of mathematical lobes that are combined to implement bidirectional scattering distribution functions (BSDFs). Bringing consistent language to this area will increase clarity in API names, textbooks, and scholarly publications. We developed this taxonomy and terminology for consistency across our own upcoming works. The taxonomy corresponds to the major BSDF implementation branches in a renderer, rather than surface appearance, and is consistent with physical considerations. The terminology aligns as closely as possible with previous work in rendering and adjacent fields, while resolving inconsistencies among them. The taxonomy is not intended for art direction, machine vision research, optics, material/lighting engineering, or other areas where the critical distinctions between materials differ from those needed by a renderer.