We review methods designed to compute correspondences between geometric shapes
represented by triangle meshes, contours or point sets. This survey is motivated in part by …

Proof: Suppose two distinct points have equal GPS values. Then their eigenfunctions have
equal value at these points. Thus given any function f, the eigenfunction expansion of f will …

Shape descriptor is a concise yet informative representation that provides a 3D object with
an identification as a member of some category. This paper developed a concise deep …

Most attempts to represent 3D shapes for deep learning have focused on volumetric grids,
multi-view images and point clouds. In this paper we look at the most popular representation …

This paper presents a comprehensive review and analysis of recent spectral shape
descriptors for nonrigid 3D shape retrieval. More specifically, we compare the latest spectral …

One of the core tasks in social network analysis is to predict the formation of links (ie various
types of relationships) over time. Previous research has generally represented the social …

Shape analysis plays a pivotal role in a large number of applications, ranging from
traditional geometry processing to more recent 3D content management. In this scenario …

In this paper, the problem of non-rigid shape recognition is studied from the perspective of
metric geometry. In particular, we explore the applicability of diffusion distances within the …

Complex geometric variations of 3D models usually pose great challenges in 3D shape
matching and retrieval. In this paper, we propose a novel 3D shape feature learning method …

Complex geometric structural variations of 3D models usually pose great challenges in 3D
shape matching and retrieval. In this paper, we propose a high-level shape feature learning …