@inproceedings{0784a469dd004fb4a818f95175ac0132,
title = "Efficient deformable shape correspondence via kernel matching",
abstract = "We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-wise and point-wise descriptors, imposing a continuity prior on the mapping, and propose a projected descent optimization procedure inspired by difference of convex functions (DC) programming.",
keywords = "Non-Rigid-Shapes, Shape-Correspondence",
author = "Matthias Vestner and Zorah Lahner and Amit Boyarski and Or Litany and Ron Slossberg and Tal Remez and Emanuele Rodola and Alex Bronstein and Michael Bronstein and Ron Kimmel and Daniel Cremers",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 7th IEEE International Conference on 3D Vision, 3DV 2017 ; Conference date: 10-10-2017 Through 12-10-2017",
year = "2018",
month = may,
day = "25",
doi = "10.1109/3DV.2017.00065",
language = "الإنجليزيّة",
series = "Proceedings - 2017 International Conference on 3D Vision, 3DV 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "517--526",
booktitle = "Proceedings - 2017 International Conference on 3D Vision, 3DV 2017",
address = "الولايات المتّحدة",
}