DC Field | Value | Language |
dc.contributor.author | Lim, I. | |
dc.contributor.author | Dielen, A. | |
dc.contributor.author | Campen, M. | |
dc.contributor.author | Kobbelt, L. | |
dc.contributor.editor | Leal-Taixe, L. | |
dc.contributor.editor | Roth, S. | |
dc.date.accessioned | 2021-12-23T16:33:42Z | - |
dc.date.available | 2021-12-23T16:33:42Z | - |
dc.date.issued | 2019 | |
dc.identifier.isbn | 9783030110147 | |
dc.identifier.issn | 03029743 | |
dc.identifier.uri | https://osnascholar.ub.uni-osnabrueck.de/handle/unios/17814 | - |
dc.description | Conference of 15th European Conference on Computer Vision, ECCV 2018 ; Conference Date: 8 September 2018 Through 14 September 2018; Conference Code:219419 | |
dc.description.abstract | The question of representation of 3D geometry is of vital importance when it comes to leveraging the recent advances in the field of machine learning for geometry processing tasks. For common unstructured surface meshes state-of-the-art methods rely on patch-based or mapping-based techniques that introduce resampling operations in order to encode neighborhood information in a structured and regular manner. We investigate whether such resampling can be avoided, and propose a simple and direct encoding approach. It does not only increase processing efficiency due to its simplicity – its direct nature also avoids any loss in data fidelity. To evaluate the proposed method, we perform a number of experiments in the challenging domain of intrinsic, non-rigid shape correspondence estimation. In comparisons to current methods we observe that our approach is able to achieve highly competitive results. © Springer Nature Switzerland AG 2019. | |
dc.description.sponsorship | Seventh Framework ProgrammeSeventh Framework Programme,FP7; Acknowledgements. The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement n◦ [340884]. We would like to thank the authors of related work [3,17] for making their implementations available, as well as the reviewers for their insightful comments. | |
dc.language.iso | en | |
dc.publisher | Springer Verlag | |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
dc.subject | Encoding (symbols) | |
dc.subject | Learning on graphs | |
dc.subject | Learning systems, Geometry processing | |
dc.subject | Neighborhood information | |
dc.subject | Non-rigid shapes | |
dc.subject | Shape correspondence estimation | |
dc.subject | Shape correspondences | |
dc.subject | Simple approach | |
dc.subject | State-of-the-art methods | |
dc.subject | Unstructured surface mesh, Computer vision | |
dc.title | A simple approach to intrinsic correspondence learning on unstructured 3D meshes | |
dc.type | conference paper | |
dc.identifier.doi | 10.1007/978-3-030-11015-4_26 | |
dc.identifier.scopus | 2-s2.0-85061747277 | |
dc.identifier.url | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061747277&doi=10.1007%2f978-3-030-11015-4_26&partnerID=40&md5=b18e3fb42afd79789043ec8b4654cc3d | |
dc.description.volume | 11131 LNCS | |
dc.description.startpage | 349 | |
dc.description.endpage | 362 | |
dcterms.isPartOf.abbreviation | Lect. Notes Comput. Sci. | |
crisitem.author.dept | FB 06 - Mathematik/Informatik | - |
crisitem.author.deptid | fb06 | - |
crisitem.author.orcid | 0000-0003-2340-3462 | - |
crisitem.author.parentorg | Universität Osnabrück | - |
crisitem.author.netid | CaMa281 | - |