Non‐rigid registration computes an alignment between a source surface with a target
surface in a non‐rigid manner. In the past decade, with the advances in 3D sensing …

Important new developments have appeared since the most recent direct survey on shape
correspondence published almost a decade ago. Our survey covers the period from 2011 …

While the ready availability of 3D scan data has influenced research throughout computer
vision, less attention has focused on 4D data; that is 3D scans of moving non-rigid objects …

We present a simple and efficient method for refining maps or correspondences by iterative
upsampling in the spectral domain that can be implemented in a few lines of code. Our main …

We propose a novel learning-based approach for robust 3D shape matching. Our method
builds upon deep functional maps and can be trained in a fully unsupervised manner …

We propose a novel 3D shape correspondence method based on the iterative alignment of
so-called smooth shells. Smooth shells define a series of coarse-to-fine shape …

This paper studies the problem of matching two complete graphs with edge weights
correlated through latent geometries, extending a recent line of research on random graph …

Graph matching, also known as network alignment, aims at recovering the latent vertex
correspondence between two unlabeled, edge-correlated weighted graphs. To tackle this …

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 …

Matching deformable 3D shapes under partiality transformations is a challenging problem
that has received limited focus in the computer vision and graphics communities. With this …