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    Deep Compositional Denoising for High-quality Monte Carlo Rendering 

    Zhang, Xianyao; Manzi, Marco; Vogels, Thijs; Dahlberg, Henrik; Gross, Markus; Papas, Marios (The Eurographics Association and John Wiley & Sons Ltd., 2021)
    We propose a deep-learning method for automatically decomposing noisy Monte Carlo renderings into components that kernelpredicting denoisers can denoise more effectively. In our model, a neural decomposition module learns ...
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    Deep Reconstruction of 3D Smoke Densities from Artist Sketches 

    Kim, Byungsoo; Huang, Xingchang; Wuelfroth, Laura; Tang, Jingwei; Cordonnier, Guillaume; Gross, Markus; Solenthaler, Barbara (The Eurographics Association and John Wiley & Sons Ltd., 2022)
    Creative processes of artists often start with hand-drawn sketches illustrating an object. Pre-visualizing these keyframes is especially challenging when applied to volumetric materials such as smoke. The authored 3D density ...
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    Automatic Feature Selection for Denoising Volumetric Renderings 

    Zhang, Xianyao; Ott, Melvin; Manzi, Marco; Gross, Markus; Papas, Marios (The Eurographics Association and John Wiley & Sons Ltd., 2022)
    We propose a method for constructing feature sets that significantly improve the quality of neural denoisers for Monte Carlo renderings with volumetric content. Starting from a large set of hand-crafted features, we propose ...

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    Author
    Gross, Markus (3)
    Manzi, Marco (2)Papas, Marios (2)Zhang, Xianyao (2)Cordonnier, Guillaume (1)Dahlberg, Henrik (1)Huang, Xingchang (1)Kim, Byungsoo (1)Ott, Melvin (1)Solenthaler, Barbara (1)... View MoreSubject
    Neural networks (3)
    Computing methodologies (2)CCS Concepts: Computing methodologies --> Ray tracing; Feature selection; Neural networks (1)CCS Concepts: Computing methodologies --> Shape modeling; Neural networks (1)Computing methodologies --> Ray tracing (1)Feature selection (1)Ray tracing (1)Shape modeling (1)... View MoreDate Issued2022 (2)2021 (1)Has File(s)true (3)

    Eurographics Association copyright © 2013 - 2023 
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