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10.1145/3641236.3664424acmconferencesArticle/Chapter ViewAbstractPublication PagessiggraphConference Proceedingsconference-collections
abstract

demoConstruct: Democratizing Scene Construction for Digital Twins through Progressive Reconstruction

Published: 13 July 2024 Publication History

Abstract

We introduce demoConstruct, an open-source project aimed at developing an accessible collaborative scene authoring tool for immersive applications, catering to both professional and untrained users. The tool employs progressive reconstruction, enabling simultaneous near real-time scene acquisition and editing tasks, including editing in Virtual Reality (VR). And, can be applied to multiple use cases, such as reconstructing disaster struck areas in near real-time for remote responders to plan and simulate operations. Participants will have the opportunity to experience an alpha version of demoConstruct, allowing them to construct their immersive environments during the lab. This experience aims to foster academic discourse and stimulate discussions to collectively advance this research area through an open-source initiative.

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References

[1]
Leon Foo, Songjia Shen, Ambrose Wee, and Chek Tien Tan. 2023. Progressive 3D Reconstruction for Collaborative Construction of Digital Twins. Proceedings of the AAAI 2023 Summer Symposium on AI x Metaverse (2023).
[2]
Carsten Griwodz, Simone Gasparini, Lilian Calvet, Pierre Gurdjos, Fabien Castan, Benoit Maujean, Gregoire De Lillo, and Yann Lanthony. 2021. AliceVision Meshroom: An open-source 3D reconstruction pipeline. In Proceedings of the 12th ACM Multimedia Systems Conference - MMSys ’21. ACM Press.
[3]
Mathieu Labbé and François Michaud. 2019. RTAB-Map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation. Journal of field robotics 36, 2 (2019), 416–446.
[4]
Katja Schwarz, Yiyi Liao, Michael Niemeyer, and Andreas Geiger. 2020. GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis. In Advances in Neural Information Processing Systems. NeurIPS.

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Published In

cover image ACM Conferences
SIGGRAPH '24: ACM SIGGRAPH 2024 Labs
July 2024
27 pages
ISBN:9798400705182
DOI:10.1145/3641236
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 July 2024

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Author Tags

  1. 3D Reconstruction
  2. Collaborative Scene Authoring

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  • Abstract
  • Research
  • Refereed limited

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  • Singapore Institute of Technology

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SIGGRAPH '24
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Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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