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CAD-Deform: Deformable Fitting of CAD Models to 3D Scans

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12358)

Abstract

Shape retrieval and alignment are a promising avenue towards turning 3D scans into lightweight CAD representations that can be used for content creation such as mobile or AR/VR gaming scenarios. Unfortunately, CAD model retrieval is limited by the availability of models in standard 3D shape collections (e.g., ShapeNet). In this work, we address this shortcoming by introducing CAD-Deform (The code for the project: https://github.com/alexeybokhovkin/CAD-Deform), a method which obtains more accurate CAD-to-scan fits by non-rigidly deforming retrieved CAD models. Our key contribution is a new non-rigid deformation model incorporating smooth transformations and preservation of sharp features, that simultaneously achieves very tight fits from CAD models to the 3D scan and maintains the clean, high-quality surface properties of hand-modeled CAD objects. A series of thorough experiments demonstrate that our method achieves significantly tighter scan-to-CAD fits, allowing a more accurate digital replica of the scanned real-world environment while preserving important geometric features present in synthetic CAD environments.

Keywords

Scene reconstruction Mesh deformation 

Notes

Acknowledgements

The authors acknowledge the usage of the Skoltech CDISE HPC cluster Zhores for obtaining the results presented in this paper. The work was partially supported by the Russian Science Foundation under Grant 19-41-04109.

Supplementary material

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Skolkovo Institute of Science and TechnologyMoscowRussia
  2. 2.Technical University of MunichMunichGermany
  3. 3.New York UniversityNew YorkUSA

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