DeepMaterialInsights: A Web-based Framework Harnessing Deep Learning for Estimation, Visualization, and Export of Material Assets from Images

Saptarshi Neil Sinha, Felix Gorsclüter, Holger Graf, Michael Weinmann

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

Accurately replicating the appearance of real-world materials in computer graphics is a complex task due to the intricate interactions between light, reflectance, and geometry. In this paper we address the challenges of material representation, acquisition, and editing by leveraging the potential of deep learning algorithms our framework provide. To enable the visualization and generation of material assets from single or multi-view images, allowing for the estimation of materials from real world objects. Additionally, a material asset exporter, enabling the export of materials in widely used formats and facilitating easy editing using common content creator tools. The proposed framework enables designers to effectively collaborate and seamlessly integrate deep learning-based material estimation models into their design pipelines using traditional content creation tools. An analysis of the performance and memory usage of material assets at various texture resolutions shows that our framework can be used plausibly according to the needs of the end-user.

Original languageEnglish
Title of host publicationProceedings - Web3D 2024
Subtitle of host publication29th International ACM Conference on 3D Web Technology
EditorsStephen N. Spencer
PublisherACM
ISBN (Electronic)9798400706899
DOIs
Publication statusPublished - 2024
Event29th International ACM Conference on 3D Web Technology, Web3D 2024 - Guimaraes, Portugal
Duration: 25 Sept 202427 Sept 2024

Publication series

NameProceedings - Web3D 2024: 29th International ACM Conference on 3D Web Technology

Conference

Conference29th International ACM Conference on 3D Web Technology, Web3D 2024
Country/TerritoryPortugal
CityGuimaraes
Period25/09/2427/09/24

Keywords

  • 3D graphics on the web
  • Deep image based BRDF estimation

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