activity
20172022
most citedEfficient Deformable Shape Correspondence via Kernel Matching

25 citations · 29 across the 2 of their papers we have counts for

collaborators

6 papers

quant-ph20224 cited

QuAnt: Quantum Annealing with Learnt Couplings

Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk +3

Modern quantum annealers can find high-quality solutions to combinatorial optimisation objectives given as quadratic unconstrained binary optimisation (QUBO) problems. Unfortunatel…

cs.CV2021

Q-Match: Iterative Shape Matching via Quantum Annealing

Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik +3

Finding shape correspondences can be formulated as an NP-hard quadratic assignment problem (QAP) that becomes infeasible for shapes with high sampling density. A promising research…

cs.CV2020

Unsupervised Dense Shape Correspondence using Heat Kernels

Mehmet Aygün, Zorah Lähner, Daniel Cremers

In this work, we propose an unsupervised method for learning dense correspondences between shapes using a recent deep functional map framework. Instead of depending on ground-truth…

cs.GR2018

Functional Maps Representation on Product Manifolds

Emanuele Rodolà, Zorah Lähner, Alex M. Bronstein +2

We consider the tasks of representing, analyzing and manipulating maps between shapes. We model maps as densities over the product manifold of the input shapes; these densities can…

cs.CV2018

Divergence-Free Shape Interpolation and Correspondence

Marvin Eisenberger, Zorah Lähner, Daniel Cremers

We present a novel method to model and calculate deformation fields between shapes embedded in . Our framework combines naturally interpolating the two input shapes a…

cs.CV201725 cited

Efficient Deformable Shape Correspondence via Kernel Matching

Zorah Lähner, Matthias Vestner, Amit Boyarski +8

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-…