The AIM@SHAPE Shape Repository is a shared repository populated with a collection of digital shapes. It is an integral part of the e-Science framework of tools and services for modeling, processing and interpreting digital shapes, developed within the AIM@SHAPE project. Our goal is to include a variety of standard test cases and benchmarks, so as to enable efficient prototyping as well as practical evaluation on real-world and large-scale shape models. The emphasis is on `certified shapes’ whose properties are additionally reflected in accompanying metadata specifed by shape ontologies developed by the AIM@SHAPE consortium. Incorporation of shape processing tools from the AIM@SHAPE Software Repository currently allows us to automatically extract metadata from certain shape categories. Additionally, we now offer some shape cateogires in multi-resolution format. Supported shapes can be downloaded at the desired Level of Detail (LOD) and file format. You can use the menu frame on the left to view and download models from the repository. Registered users can upload new shape models, and can see their profile page. Please consult the FAQ and news page for more information.

References in zbMATH (referenced in 18 articles )

Showing results 1 to 18 of 18.
Sorted by year (citations)

  1. Yeung, Yu-Hong; Pothen, Alex; Crouch, Jessica: AMPS: real-time mesh cutting with augmented matrices for surgical simulations. (2020)
  2. Pernot, Jean-Philippe; Michelucci, Dominique; Daniel, Marc; Foufou, Sebti: Towards a better integration of modelers and black box constraint solvers within the product design process (2019)
  3. Dimitrov, P.; Vakarelov, P.: Dynamic contact algebras and quantifier-free logics for space and time (2018)
  4. Gessner, Samuel (ed.); Hashagen, Ulf (ed.); Peiffer, Jeanne (ed.); Tournès, Dominique (ed.): Mathematical instruments between material artifacts and ideal machines: their scientific and social role before 1950. Abstracts from the workshop held December 17--23, 2017 (2017)
  5. Hoeher, P. A.: OFDM data detection and channel estimation (2017)
  6. King, Nathan D.; Ruuth, Steven J.: Solving variational problems and partial differential equations that map between manifolds via the closest point method (2017)
  7. Lei, Na; Zheng, Xiaopeng; Luo, Zhongxuan; Gu, David Xianfeng: Quadrilateral and hexahedral mesh generation based on surface foliation theory. II (2017)
  8. Jia, Zhongxiao; Lin, Wen-Wei; Liu, Ching-Sung: A positivity preserving inexact Noda iteration for computing the smallest eigenpair of a large irreducible (M)-matrix (2015)
  9. Böckle, Gebhard: Cohomological theory of crystals over function fields and applications (2014)
  10. Athanasiadis, Theodoros; Fudos, Ioannis; Nikou, Christophoros; Stamati, Vasiliki: Feature-based 3D morphing based on geometrically constrained spherical parameterization (2012)
  11. Boulanger, Anne-Céline; Cancès, Clément; Mathis, Hélène; Saleh, Khaled; Seguin, Nicolas: OSAMOAL: Optimized Simulations by Adapted MOdels using Asymptotic Limits (2012)
  12. Gloria, Antoine: Numerical homogenization: survey, new results, and perspectives (2012)
  13. Giorgi, D.; Frosini, P.; Spagnuolo, M.; Falcidieno, B.: 3D relevance feedback via multilevel relevance judgements (2010) ioport
  14. MacDonald, Colin B.; Ruuth, Steven J.: The implicit closest point method for the numerical solution of partial differential equations on surfaces (2009)
  15. Vartziotis, Dimitris; Wipper, Joachim; Schwald, Bernd: The geometric element transformation method for tetrahedral mesh smoothing (2009)
  16. Albertoni, Riccardo; De Martino, Monica: Asymmetric and context-dependent semantic similarity among ontology instances (2008)
  17. Macdonald, Colin B.; Ruuth, Steven J.: Level set equations on surfaces via the closest point method (2008)
  18. Shamir, Ariel: A survey on mesh segmentation techniques (2008)