Neural Stochastic Screened Poisson Reconstruction
SIGGRAPH Asia 2023
Abstract
Reconstructing a surface from a point cloud is an underdetermined problem. We use a neural network to study and quantify this reconstruction uncertainty under a Poisson smoothness prior. Our algorithm addresses the main limitations of existing work and can be fully integrated into the 3D scanning pipeline, from obtaining an initial reconstruction to deciding on the next best sensor position and updating the reconstruction upon capturing more data.
Links
BibTex
@article{sellan2023neural,
title = {Neural Stochastic Screened Poisson Reconstruction},
author = {Silvia Sellán and Alec Jacobson},
year = {2023},
journal = {ACM Transactions on Graphics (Proc. SIGGRAPH Asia)}
}
Acknowledgements
This project is funded in part by NSERC Discovery (RGPIN2017-05235, RGPAS-2017-507938), New Frontiers of Research Fund (NFRFE-201), the Ontario Early Research Award program, the Canada Research Chairs Program, a Sloan Research Fellowship and the DSI Catalyst Grant program. The first author is funded in part by an NSERC Vanier Scholarship.
We thank Kirill Serkh, Kiriakos Kutulakos, David Lindell, Eitan Grinspun, David I.W. Levin, Oded Stein, Andrea Tagliasacchi, Otman Benchekroun, Lily Goli and Claas A. Voelcker for insightful conversations that inspired us in this work; Hsueh-Ti Derek Liu for his help rendering our results; as well as Rafael Rodrigues (Fig. 6, CC BY-NC-SA 4.0) and ShaggyDude (Fig. 13, CC BY 4.0) for releasing their 3D models for academic use. We would also like to thank Xuan Dam, John Hancock and all the University of Toronto Department of Computer Science research, administrative and maintenance staff.
We thank Kirill Serkh, Kiriakos Kutulakos, David Lindell, Eitan Grinspun, David I.W. Levin, Oded Stein, Andrea Tagliasacchi, Otman Benchekroun, Lily Goli and Claas A. Voelcker for insightful conversations that inspired us in this work; Hsueh-Ti Derek Liu for his help rendering our results; as well as Rafael Rodrigues (Fig. 6, CC BY-NC-SA 4.0) and ShaggyDude (Fig. 13, CC BY 4.0) for releasing their 3D models for academic use. We would also like to thank Xuan Dam, John Hancock and all the University of Toronto Department of Computer Science research, administrative and maintenance staff.