Registration is a transformation estimation problem between two point clouds, which has a
unique and critical role in numerous computer vision applications. The developments of …

This review provides a comprehensive overview of the state-of-the-art methods of graph-
based networks from a deep learning perspective. Graph networks provide a generalized …

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

As a fundamental and critical task in various visual applications, image matching can identify
then correspond the same or similar structure/content from two or more images. Over the …

Combinatorial optimization is a well-established area in operations research and computer
science. Until recently, its methods have focused on solving problem instances in isolation …

In recent years, algorithms and neural architectures based on the Weisfeiler-Leman
algorithm, a well-known heuristic for the graph isomorphism problem, have emerged as a …

Abstract Graph Neural Networks (GNNs) with attention have been successfully applied for
learning visual feature matching. However, current methods learn with complete graphs …

Matching local features across images is a fundamental problem in computer vision.
Targeting towards high accuracy and efficiency, we propose Seeded Graph Matching …

As a bridge between language and vision domains, cross-modal retrieval between images
and texts is a hot research topic in recent years. It remains challenging because the current …

Image-text retrieval is a fundamental cross-modal task whose main idea is to learn image-
text matching. Generally, according to whether there exist interactions during the retrieval …