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 …

Non‐rigid registration computes an alignment between a source surface with a target
surface in a non‐rigid manner. In the past decade, with the advances in 3D sensing …

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 …

Infrared images can distinguish targets from their backgrounds based on the radiation
difference, which works well in all-weather and all-day/night conditions. By contrast, visible …

In image fusion, the most desirable information is obtained from multiple images of the same
scene and merged to generate a composite image. This resulting new image is more …

This letter introduces a robust representation of 3-D shapes, named DeepPano, learned with
deep convolutional neural networks (CNN). Firstly, each 3-D shape is converted into a …

Feature matching, which refers to establishing reliable correspondences between two sets
of feature points, is a critical prerequisite in feature-based image registration. This paper …

Feature matching, which refers to establishing reliable correspondence between two sets of
features (particularly point features), is a critical prerequisite in feature-based registration. In …

In previous work on point registration, the input point sets are often represented using
Gaussian mixture models and the registration is then addressed through a probabilistic …

Feature matching, which refers to establishing reliable correspondence between two sets of
features, is a critical prerequisite in a wide spectrum of vision-based tasks. Existing attempts …