“demoConstruct: Democratizing Scene Construction for Digital Twins Through Progressive Reconstruction”
Conference:
Type(s):
Title:
- demoConstruct: Democratizing Scene Construction for Digital Twins Through Progressive Reconstruction
Program Title:
- Labs Installations
Organizer(s)/Presenter(s):
Description:
demoConstruct aims to provide user-friendly and accessible collaborative 3D scene acquisition and editing methods for creating digital twins, through the use of progressive 3D reconstruction methods. Participants will collaboratively view and author immersive environments during the lab in near-real-time, using different devices such as mobile, VR HMD, and laptops.
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 Labb? and Fran?ois 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.
ACM Digital Library Publication:
- demoConstruct: Democratizing Scene Construction for Digital Twins Through Progressive Reconstruction
