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 …

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 …

Estimating correspondence between two shapes continues to be a challenging problem in
geometry processing. Most current methods assume deformation to be near-isometric …

In deformable registration, the Riemannian framework–Large Deformation Diffeomorphic
Metric Map**, or LDDMM for short–has inspired numerous techniques for comparing …

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 …

We present a novel surface convolution operator acting on vector fields that is based on a
simple observation: instead of combining neighboring features with respect to a single …

We present an automated technique for computing a map between two genus‐zero shapes,
which matches semantically corresponding regions to one another. Lack of annotated data …

Finding correspondences between shapes is a fundamental problem in computer vision and
graphics, which is relevant for many applications, including 3D reconstruction, object …

A high-fidelity digital representation of (part of) the human body is a key enabler for
integrating humans in a digital twin. Among different parts of human body, building the …