With the explosion in the number of digital images taken every day, the demand for more
accurate and visually pleasing images is increasing. However, the images captured by …

As a convex relaxation of the low rank matrix factorization problem, the nuclear norm
minimization has been attracting significant research interest in recent years. The standard …

Most popular clustering methods map raw image data into a projection space in which the
clustering assignment is obtained with the vanilla k-means approach. In this article, we …

Infrared search and track (IRST) system is widely used in many fields, however, it's still a
challenging task to detect infrared small targets in complex background. This paper …

Under the framework of graph-based learning, the key to robust subspace clustering and
subspace learning is to obtain a good similarity graph that eliminates the effects of errors …

The correction of exposure-related issues is a pivotal component in enhancing the quality of
images, offering substantial implications for various computer vision tasks. Historically, most …

Given a single outdoor image, this paper proposes a collaborative learning approach for
labeling it as either sunny or cloudy. Never adequately addressed, this twoclass …

Multi-view data is very popular in real-world applications, as different view-points and
various types of sensors help to better represent data when fused across views or …