2013
DOI: 10.1145/2461912.2462009
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Global illumination with radiance regression functions

Abstract: c) (a) (b) Figure 1: Real-time rendering results with radiance regression functions for scenes with glossy interreflections (a), multiple local lights (b), and complex geometry and materials (c). AbstractWe present radiance regression functions for fast rendering of global illumination in scenes with dynamic local light sources. A radiance regression function (RRF) represents a non-linear mapping from local and contextual attributes of surface points, such as position, viewing direction, and lighting condition… Show more

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Cited by 103 publications
(85 citation statements)
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“…Lastly, one of the promising approaches uses Precomputed Light Transport (PLT) for rendering complex scenes with a full indirect illumination in real-time and the ability to dynamically control local lights and viewing directions [112]. The approach uses radiance regression function to train the neural network in precomputation phase to allow real-time rendering of the indirect illumination of the whole scene under different lighting and viewing conditions.…”
Section: Types Of Simulations/analysesmentioning
confidence: 99%
“…Lastly, one of the promising approaches uses Precomputed Light Transport (PLT) for rendering complex scenes with a full indirect illumination in real-time and the ability to dynamically control local lights and viewing directions [112]. The approach uses radiance regression function to train the neural network in precomputation phase to allow real-time rendering of the indirect illumination of the whole scene under different lighting and viewing conditions.…”
Section: Types Of Simulations/analysesmentioning
confidence: 99%
“…Ren et al [30] proposed Radiance Regression Functions which use an ANN to approximate the indirect illumination at every scene point in a computationally effective way. Their model is a nonlinear 6D radiance regression function which takes surface position, view direction and lighting direction as input and returns the RGB colour of the indirect illumination.…”
Section: Artificial Neural Networkmentioning
confidence: 99%
“…This limits the use cases to scenes where the irradiance can be precomputed. Ren et al describes an approach that uses radiance regression functions to compute global illumination using a neural network [41]. The underlying idea is similar to our approach but the method requires extensive pre-processing per scene and is limited to static geometry.…”
Section: Related Workmentioning
confidence: 99%