Parsing geometry using structure-aware shape templates

Vignesh Ganapathi-Subramanian, Olga Diamanti, Soeren Pirk, Chengcheng Tang, Matthias Niessner, Leonidas Guibas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

26 Scopus citations


Real-life man-made objects often exhibit strong and easily-identifiable structure, as a direct result of their design or their intended functionality. Structure typically appears in the form of individual parts and their arrangement. Knowing about object structure can be an important cue for object recognition and scene understanding - a key goal for various AR and robotics applications. However, commodity RGB-D sensors used in these scenarios only produce raw, unorganized point clouds, without structural information about the captured scene. Moreover, the generated data is commonly partial and susceptible to artifacts and noise, which makes inferring the structure of scanned objects challenging. In this paper, we organize large shape collections into parameterized shape templates to capture the underlying structure of the objects. The templates allow us to transfer the structural information onto new objects and incomplete scans. We employ a deep neural network that matches the partial scan with one of the shape templates, then match and fit it to complete and detailed models from the collection. This allows us to faithfully label its parts and to guide the reconstruction of the scanned object. We showcase the effectiveness of our method by comparing it to other state-of-the-art approaches.

Original languageEnglish
Title of host publicationProceedings - 2018 International Conference on 3D Vision, 3DV 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages10
ISBN (Electronic)9781538684252
StatePublished - 12 Oct 2018
Externally publishedYes
Event6th International Conference on 3D Vision, 3DV 2018 - Verona, Italy
Duration: 5 Sep 20188 Sep 2018

Publication series

NameProceedings - 2018 International Conference on 3D Vision, 3DV 2018


Conference6th International Conference on 3D Vision, 3DV 2018


  • Partial Shape Recovery
  • Shape Primitives
  • Shape Reconstruction
  • Shape Templates
  • Template Fitting


Dive into the research topics of 'Parsing geometry using structure-aware shape templates'. Together they form a unique fingerprint.

Cite this