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Authors: Radu Alexandru Rosu and Sven Behnke

Affiliation: Autonomous Intelligent Systems, University of Bonn, Germany

Keyword(s): Physically-based Rendering, Synthetic Data Generation, Visualization Toolkit.

Abstract: Modern rendering libraries provide unprecedented realism, producing real-time photorealistic 3D graphics on commodity hardware. Visual fidelity, however, comes at the cost of increased complexity and difficulty of usage, with many rendering parameters requiring a deep understanding of the pipeline. We propose EasyPBR as an alternative rendering library that strikes a balance between ease-of-use and visual quality. EasyPBR consists of a deferred renderer that implements recent state-of-the-art approaches in physically based rendering. It offers an easy-to-use Python and C++ interface that allows high-quality images to be created in only a few lines of code or directly through a graphical user interface. The user can choose between fully controlling the rendering pipeline or letting EasyPBR automatically infer the best parameters based on the current scene composition. The EasyPBR library can help the community to more easily leverage the power of current GPUs to create realistic image s. These can then be used as synthetic data for deep learning or for creating animations for academic purposes. (More)

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Paper citation in several formats:
Rosu, R. and Behnke, S. (2021). EasyPBR: A Lightweight Physically-based Renderer. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - GRAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 245-252. DOI: 10.5220/0010268902450252

@conference{grapp21,
author={Radu Alexandru Rosu. and Sven Behnke.},
title={EasyPBR: A Lightweight Physically-based Renderer},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - GRAPP},
year={2021},
pages={245-252},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010268902450252},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - GRAPP
TI - EasyPBR: A Lightweight Physically-based Renderer
SN - 978-989-758-488-6
IS - 2184-4321
AU - Rosu, R.
AU - Behnke, S.
PY - 2021
SP - 245
EP - 252
DO - 10.5220/0010268902450252
PB - SciTePress

- Science and Technology Publications, Lda.
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