Browsing by Author "Krivánek, Jaroslav"

Now showing 1 - 5 of 5
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    Implementing One-Click Caustics in Corona Renderer
    (The Eurographics Association, 2019) Šik, Martin; Krivánek, Jaroslav; Boubekeur, Tamy and Sen, Pradeep
    This paper describes the implementation of a fully automatic caustics rendering solution in Corona Renderer. The main requirement is that the technique be completely transparent to the user, should not need any parameter setting at all, and be fully integrated into the interactive and progressive rendering workflow. We base our approach on an efficient subset of the vertex connection and merging algorithm, specifically a multiple importance sampling combination of path tracing and photon mapping. We rely on Metropolis sampling to guide photon paths into the relevant parts of the scene. While these underlying ideas have appeared in existing research work, numerous previously unaddressed issues and edge cases arise when one applies these ideas in practice. These include unreliable convergence of the Metropolis sampler in scenes with many light sources of different sizes and intensities, the ''caustic in a stadium'' problem (i.e., efficient rendering of small caustics in extremely large scenes), etc. We present the solutions we have developed to address such issues, yielding what we call ''one-click caustics rendering''. User feedback suggests that our approach substantially improves usability over methods previously implemented in comercially available software, all requiring the user to set various technical parameters.
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    A Multiscale Microfacet Model Based on Inverse Bin Mapping
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Atanasov, Asen; Wilkie, Alexander; Koylazov, Vladimir; Krivánek, Jaroslav; Mitra, Niloy and Viola, Ivan
    Accurately controllable shading detail is a crucial aspect of realistic appearance modelling. Two fundamental building blocks for this are microfacet BRDFs, which describe the statistical behaviour of infinitely small facets, and normal maps, which provide user-controllable spatio-directional surface features. We analyse the filtering of the combined effect of a microfacet BRDF and a normal map. By partitioning the half-vector domain into bins we show that the filtering problem can be reduced to evaluation of an integral histogram (IH), a generalization of a summed-area table (SAT). Integral histograms are known for their large memory requirements, which are usually proportional to the number of bins. To alleviate this, we introduce Inverse Bin Maps, a specialised form of IH with a memory footprint that is practically independent of the number of bins. Based on these, we present a memory-efficient, production-ready approach for filtering of high resolution normal maps with arbitrary Beckmann flake roughness. In the corner case of specular normal maps (zero, or very small roughness values) our method shows similar convergence rates to the current state of the art, and is also more memory efficient.
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    Neural Acceleration of Scattering-Aware Color 3D Printing
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Rittig, Tobias; Sumin, Denis; Babaei, Vahid; Didyk, Piotr; Voloboy, Alexey; Wilkie, Alexander; Bickel, Bernd; Myszkowski, Karol; Weyrich, Tim; Krivánek, Jaroslav; Mitra, Niloy and Viola, Ivan
    With the wider availability of full-color 3D printers, color-accurate 3D-print preparation has received increased attention. A key challenge lies in the inherent translucency of commonly used print materials that blurs out details of the color texture. Previous work tries to compensate for these scattering effects through strategic assignment of colored primary materials to printer voxels. To date, the highest-quality approach uses iterative optimization that relies on computationally expensive Monte Carlo light transport simulation to predict the surface appearance from subsurface scattering within a given print material distribution; that optimization, however, takes in the order of days on a single machine. In our work, we dramatically speed up the process by replacing the light transport simulation with a data-driven approach. Leveraging a deep neural network to predict the scattering within a highly heterogeneous medium, our method performs around two orders of magnitude faster than Monte Carlo rendering while yielding optimization results of similar quality level. The network is based on an established method from atmospheric cloud rendering, adapted to our domain and extended by a physically motivated weight sharing scheme that substantially reduces the network size. We analyze its performance in an end-to-end print preparation pipeline and compare quality and runtime to alternative approaches, and demonstrate its generalization to unseen geometry and material values. This for the first time enables full heterogenous material optimization for 3D-print preparation within time frames in the order of the actual printing time.
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    SkyGAN: Towards Realistic Cloud Imagery for Image Based Lighting
    (The Eurographics Association, 2022) Mirbauer, Martin; Rittig, Tobias; Iser, Tomáš; Krivánek, Jaroslav; Šikudová, Elena; Ghosh, Abhijeet; Wei, Li-Yi
    Achieving photorealism when rendering virtual scenes in movies or architecture visualizations often depends on providing a realistic illumination and background. Typically, spherical environment maps serve both as a natural light source from the Sun and the sky, and as a background with clouds and a horizon. In practice, the input is either a static high-resolution HDR photograph manually captured on location in real conditions, or an analytical clear sky model that is dynamic, but cannot model clouds. Our approach bridges these two limited paradigms: a user can control the sun position and cloud coverage ratio, and generate a realistically looking environment map for these conditions. It is a hybrid data-driven analytical model based on a modified state-of-the-art GAN architecture, which is trained on matching pairs of physically-accurate clear sky radiance and HDR fisheye photographs of clouds. We demonstrate our results on renders of outdoor scenes under varying time, date, and cloud covers.
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    StyleProp: Real-time Example-based Stylization of 3D Models
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Hauptfleisch, Filip; Texler, Ondrej; Texler, Aneta; Krivánek, Jaroslav; Sýkora, Daniel; Eisemann, Elmar and Jacobson, Alec and Zhang, Fang-Lue
    We present a novel approach to the real-time non-photorealistic rendering of 3D models in which a single hand-drawn exemplar specifies its appearance. We employ guided patch-based synthesis to achieve high visual quality as well as temporal coherence. However, unlike previous techniques that maintain consistency in one dimension (temporal domain), in our approach, multiple dimensions are taken into account to cover all degrees of freedom given by the available space of interactions (e.g., camera rotations). To enable interactive experience, we precalculate a sparse latent representation of the entire interaction space, which allows rendering of a stylized image in real-time, even on a mobile device. To the best of our knowledge, the proposed system is the first that enables interactive example-based stylization of 3D models with full temporal coherence in predefined interaction space.