Imperial College London


Faculty of EngineeringDepartment of Computing

Chair in Machine Learning and Pattern Recognition



m.bronstein Website




569Huxley BuildingSouth Kensington Campus






BibTex format

author = {Vestner, M and Lahner, Z and Boyarski, A and Litany, O and Slossberg, R and Remez, T and Rodola, E and Bronstein, A and Bronstein, M and Kimmel, R and Cremers, D},
doi = {10.1109/3DV.2017.00065},
pages = {517--526},
title = {Efficient deformable shape correspondence via kernel matching},
url = {},
year = {2018}

RIS format (EndNote, RefMan)

AB - © 2017 IEEE. 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.
AU - Vestner,M
AU - Lahner,Z
AU - Boyarski,A
AU - Litany,O
AU - Slossberg,R
AU - Remez,T
AU - Rodola,E
AU - Bronstein,A
AU - Bronstein,M
AU - Kimmel,R
AU - Cremers,D
DO - 10.1109/3DV.2017.00065
EP - 526
PY - 2018///
SP - 517
TI - Efficient deformable shape correspondence via kernel matching
UR -
ER -