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 present a novel learning-based approach for computing correspondences between non-
rigid 3D shapes. Unlike previous methods that either require extensive training data or …

We introduce the first completely unsupervised correspondence learning approach for
deformable 3D shapes. Key to our model is the understanding that natural deformations …

We present a novel method for computing correspondences across 3D shapes using
unsupervised learning. Our method computes a non-linear transformation of given …

In this paper, we provide a theoretical foundation for pointwise map recovery from functional
maps and highlight its relation to a range of shape correspondence methods based on …

We introduce pointwise map smoothness via the Dirich-let energy into the functional map
pipeline, and propose an algorithm for optimizing it efficiently, which leads to highquality …

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 …

We present a novel approach for optimizing real‐valued functions based on a wide range of
topological criteria. In particular, we show how to modify a given function in order to remove …

We propose a novel discrete solver for optimizing functional map‐based energies, including
descriptor preservation and promoting structural properties such as area‐preservation …