The goal of correspondence pruning is to recognize correct correspondences (inliers) from
initial ones, with applications to various feature matching based tasks. Seeking neighbors in …

In this article, we present a feature-based remote sensing (RS) image matching method
termed progressive motion coherence (PMC). We formulate the matching problem into a …

With the continuous advancement of remote sensing (RS) technology, RS ship detection
plays a crucial role in ensuring maritime safety and the oceanic economy, but it also faces …

Building high-quality correspondences is critical in the feature-based point cloud registration
pipelines. However, existing single-sequence learning frameworks are difficult to accurately …

Navigation is of crucial importance for the wide application of unmanned aerial vehicles
(UAVs). Although methods based on the Global Positioning System (GPS) and those …

Learning correspondences aims to find correct correspondences (inliers) from the initial
correspondence set with an uneven correspondence distribution and a low inlier rate, which …

Correspondence pruning has recently drawn considerable attention as a crucial step in
image matching. Existing methods typically achieve this by constructing neighborhoods for …

Establishing high-quality correspondences is a fundamental step for many computer vision
tasks. Leveraging the local consistency of correct correspondences (ie, inliers) has been a …

Correspondence pruning aims to remove false correspondences (outliers) from an initial
putative correspondence set. This process holds significant importance and serves as a …

The success of many computer vision and pattern recognition applications depends on
matching local features on two or more images. Because the initial correspondence set—ie …