Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

Feature matching aims to identify reliable correspondences between two sets of given initial
feature points, which is of considerable importance to photogrammetry and computer vision …

Abstract While Structure from Motion achieves great success in 3D reconstruction, it still
meets challenges on large scale scenes. Incremental SfM approaches are robust to outliers …

Gaussian mixture models (GMMs) are a family of generative models used extensively in
many machine learning applications. The modeling power of GMMs is directly linked to the …

A commonly used tool for estimating the parameters of a mixture model is the Expectation–
Maximization (EM) algorithm, which is an iterative procedure that can serve as a maximum …

In this paper, we propose a Joint Representation Attention Network (JRA-Net), an end-to-
end network, to establish reliable correspondences for image pairs. The initial …

Unmanned aerial vehicles (UAVs) have been used in a wide range of applications and
become an increasingly important radar target. To better model radar data and to tackle the …

This paper presents a sonar-inertial navigation system with an adaptive grouping
optimization framework, which tightly couples inertial measurements with acoustic data from …

Seeking reliable correspondences then recovering camera poses from a set of putative
correspondences extracted from two images of the same scene is a fundamental problem in …

Automatic matching of multimodal remote sensing images remains a vital yet challenging
task, particularly for remote sensing and computer vision applications. Most traditional …