This comprehensive review provides an in-depth analysis of graph theory, various graph
types, and the role of graph visualization in scientific studies. Graphs serve as powerful tools …

Estimating accurate 3D locations of objects from monocular images is a challenging
problem because of lacking depth. Previous work shows that utilizing the object's keypoint …

Obtaining large pre-trained models that can be fine-tuned to new tasks with limited
annotated samples has remained an open challenge for medical imaging data. While pre …

The graph matching optimization problem is an essential component for many tasks in
computer vision, such as bringing two deformable objects in correspondence. Naturally, a …

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 …

Abstract Recent works apply Graph Neural Networks (GNNs) to graph matching tasks and
show promising results. Considering that model outputs are complex matchings, we devise …

Cooperative LiDAR systems integrating vehicles and road infrastructure, termed V2I
calibration, exhibit substantial potential, yet their deployment encounters numerous …

This paper focuses on the registration problem of shape graphs, where a shape graph is a
set of nodes connected by articulated curves with arbitrary shapes. This registration requires …

In the graph matching problem we observe two graphs $ G, H $ and the goal is to find an
assignment (or matching) between their vertices such that some measure of edge …

The fast advancement of Large Vision-Language Models (LVLMs) has shown immense
potential. These models are increasingly capable of tackling abstract visual tasks. Geometric …