arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2012.03325cs.GR
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EasyPBR:一个轻量级的基于物理的渲染器

EasyPBR: A Lightweight Physically-Based Renderer

Radu Alexandru Rosu, Sven Behnke

摘要:

现代渲染库提供了前所未有的真实感,在商用硬件上生成实时照片级逼真的3D图形。然而,视觉保真度的代价是增加了复杂性和使用难度,许多渲染参数需要对管道有深入的了解。我们提出EasyPBR作为替代渲染库,在易用性和视觉质量之间取得平衡。EasyPBR由一个延迟渲染器组成,该渲染器在基于物理的渲染中实现了最新的最先进的方法。它提供了一个易于使用的Python和C++界面,允许仅通过几行代码或直接通过图形用户界面创建高质量的图像。用户可以选择完全控制渲染管道或让EasyPBR根据当前场景合成自动推断最佳参数。EasyPBR库可以帮助社区更轻松地利用当前GPU的功能来创建逼真的图像。然后,这些可以用作深度学习的合成数据或用于创建用于学术目的的动画。

英文摘要:

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 images. These can then be used as synthetic data for deep learning or for creating animations for academic purposes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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