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Deep Adaptive Sampling for Low Sample Count Rendering
(The Eurographics Association and John Wiley & Sons Ltd., 2018)
Recently, deep learning approaches have proven successful at removing noise from Monte Carlo (MC) rendered images at extremely low sampling rates, e.g., 1-4 samples per pixel (spp). While these methods provide dramatic ...
Learning to Importance Sample in Primary Sample Space
(The Eurographics Association and John Wiley & Sons Ltd., 2019)
Importance sampling is one of the most widely used variance reduction strategies in Monte Carlo rendering. We propose a novel importance sampling technique that uses a neural network to learn how to sample from a desired ...
Neural Denoising with Layer Embeddings
(The Eurographics Association and John Wiley & Sons Ltd., 2020)
We propose a novel approach for denoising Monte Carlo path traced images, which uses data from individual samples rather than relying on pixel aggregates. Samples are partitioned into layers, which are filtered separately, ...
Photorealistic Material Editing Through Direct Image Manipulation
(The Eurographics Association and John Wiley & Sons Ltd., 2020)
Creating photorealistic materials for light transport algorithms requires carefully fine-tuning a set of material properties to achieve a desired artistic effect. This is typically a lengthy process that involves a trained ...
Learning Multiple-Scattering Solutions for Sphere-Tracing of Volumetric Subsurface Effects
(The Eurographics Association and John Wiley & Sons Ltd., 2021)
Accurate subsurface scattering solutions require the integration of optical material properties along many complicated light paths. We present a method that learns a simple geometric approximation of random paths in a ...
Neural Temporal Adaptive Sampling and Denoising
(The Eurographics Association and John Wiley & Sons Ltd., 2020)
Despite recent advances in Monte Carlo path tracing at interactive rates, denoised image sequences generated with few samples per-pixel often yield temporally unstable results and loss of high-frequency details. We present ...
Automatic Feature Selection for Denoising Volumetric Renderings
(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 ...
Real-time Neural Rendering of Dynamic Light Fields
(The Eurographics Association and John Wiley & Sons Ltd., 2024)
Synthesising high-quality views of dynamic scenes via path tracing is prohibitively expensive. Although caching offline-quality global illumination in neural networks alleviates this issue, existing neural view synthesis ...