Graph matching, which refers to a class of computational problems of finding an optimal
correspondence between the vertices of graphs to minimize (maximize) their node and edge …

Abstract Model fusion without accessing training data in machine learning has attracted
increasing interest due to the practical resource-saving and data privacy issues. During the …

Hypergraph matching is a useful tool to find feature correspondence by considering higher-
order structural information. Recently, the employment of deep learning has made great …

Diffusion process has advanced object retrieval greatly as it can capture the underlying
manifold structure. Recent studies have experimentally demonstrated that tensor product …

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

We present a convex relaxation for the multi-graph matching problem. Our formulation
allows for partial pairwise matchings, guarantees cycle consistency, and our objective …

This paper addresses the problem of multiple graph matching (MGM) by considering both
offline batch mode and online setting. We explore the concept of cycle-consistency over …

The matching of multiple objects (eg shapes or images) is a fundamental problem in vision
and graphics. In order to robustly handle ambiguities, noise and repetitive patterns in …

Graph matching (GM) which is the problem of finding vertex correspondence among two or
multiple graphs is a fundamental problem in computer vision and pattern recognition. GM …

Graph matching problem has been widely used in many fields. Due to the discrete property
of graph matching problem, the continuous relaxation will result in a bad influence on the …