VMV: Vision, Modeling, and Visualization

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Browsing VMV: Vision, Modeling, and Visualization by Subject "Antialiasing"

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    Alias-Free Shadows with Ray Cones for Alpha Tested Geometry
    (The Eurographics Association, 2025) Brüll, Felix; Kern, René; Grosch, Thorsten; Egger, Bernhard; Günther, Tobias
    We present a method for computing alias-free, smooth shadows for alpha-tested geometry using a single ray per pixel. Without mipmap filtering, hard shadows from alpha-tested geometry appear very noisy under camera motion. Typically, many ray samples are required to soften the shadows and reduce noise. We propose using mipmaps instead, to achieve a fast and temporally stable solution. To determine the appropriate mipmap level, we introduce novel ray cone operations that account for directional and point light sources.
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    Neural Volumetric Level of Detail for Path Tracing
    (The Eurographics Association, 2024) Stadter, Linda; Hofmann, Nikolai; Stamminger, Marc; Linsen, Lars; Thies, Justus
    We introduce a neural level of detail pipeline for use in a GPU path tracer based on a sparse volumetric representation derived from neural radiance fields. We pre-compute lighting and occlusion to train a neural radiance field which faithfully captures appearance and shading via image-based optimization. By converting the resulting neural network into an efficiently rendered representation, we eliminate costly evaluations at runtime and keep performance competitive. When applying our representation to certain areas of the scene, we trade a slight bias from gradient-based optimization and lossy volumetric conversion for highly anti-aliased results at low sample counts. This enables virtually noise-free and temporally stable results at low computational cost and without any additional post-processing, such as denoising. We demonstrate the applicability of our method to both individual objects and a challenging outdoor scene composed of highly detailed foliage.