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Research Article | Open Access

Delving into high-quality SVBRDF acquisition: A new setup and method

School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China
Guangdong Shidi Intelligence Technology, Ltd., Guangzhou 510000, China
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Graphical Abstract

Abstract

In this study, we present a new and innovative framework for acquiring high-quality SVBRDF maps. Our approach addresses the limi-tations of the current methods and proposes a new solution. The core of our method is a simple hardware setup consisting of a consumer-level camera, LED lights, and a carefully designed network that can accurately obtain the high-quality SVBRDF properties of a nearly planar object. By capturing a flexible number of images of an object, our network uses different subnetworks to train different property maps and employs appropriate loss functions for each of them. To further enhance the quality of the maps, we improved the network structure by adding a novel skip connection that connects the encoder and decoder withglobal features. Through extensive experimentation using both synthetic and real-world materials, our results demonstrate that our method outperforms previous methods and produces superior results. Furthermore, our proposed setup can also be used to acquire physically based rendering maps of special materials.

Keywords

acquisition setupSVBRDF acquisitionmaterial captureglobal skip connection

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Computational Visual Media
Volume 10 Issue 3,
June 2024
Pages 523-541
DOI: 10.1007/s41095-023-0352-6
Cite this article:
Xian C, Li J, Wu H, et al. Delving into high-quality SVBRDF acquisition: A new setup and method. Computational Visual Media, 2024, 10(3): 523-541. https://doi.org/10.1007/s41095-023-0352-6

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Received: 02 March 2023
Accepted: 20 April 2023
Published: 09 February 2024
© The Author(s) 2024.

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