Ambient Occlusion Baking via a Feed-Forward Neural Network
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
We present a feed-forward neural network approach for ambient occlusion baking in real-time rendering. The idea is based on implementing a multi-layer perceptron that allows a general encoding via regression and an efficient decoding via a simple GPU fragment shader. The non-linear nature of multi-layer perceptrons makes them suitable and effective for capturing nonlinearities described by ambient occlusion values. A multi-layer perceptron is also random-accessible, has a compact size, and can be evaluated efficiently on the GPU. We illustrate our approach of screen-space ambient occlusion based on neural network including its quality, size, and run-time speed.
Description
@inproceedings{10.2312:egsh.20171003,booktitle = {EG 2017 - Short Papers},editor = {Adrien Peytavie and Carles Bosch},title = {{Ambient Occlusion Baking via a Feed-Forward Neural Network}},author = {Erra, Ugo andCapece, Nicola Felice andAgatiello, Roberto},year = {2017},publisher = {The Eurographics Association},ISSN = {1017-4656},ISBN = {},DOI = {10.2312/egsh.20171003}}