Appearance and motion are two important sources of information in video object
segmentation (VOS). Previous methods mainly focus on using simplex solutions, lowering …

Object-oriented convolutional neural network (CNN) has been proven to be an effective
classification method for very fine spatial resolution remotely sensed imagery. It can obtain …

In this article, we present a content-sensitive superpixel generation method with edge
penalty and the contraction–expansion search strategy (EPCES) for synthetic aperture radar …

Superpixel segmentation is a fundamental computer vision technique that finds application
in a multitude of high level computer vision tasks. Most state-of-the-art superpixel …

Manual annotation of video segmentation datasets requires an immense amount of human
effort, thus, reduction of human annotation costs is an active topic of research. While many …

Superpixels are generated by automatically grouping image pixels into lots and lots of
compact segments. In computer vision, it is widely used as an effective way to reduce the …

Superpixel is one of the most popular image over-segmentations with broad applications in
the computer vision field to reduce their computations by replacing pixels as primitives. The …

A tracking-by-segmentation algorithm, which tracks and segments a target object in a video
sequence, is proposed in this paper. In the first frame, we segment out the target object in a …

As one of the most popular preprocessing steps in computer vision fields, superpixel
generation algorithm has been extensively studied in recent years. Researchers have to find …

Superpixel segmentation approach, as a preprocessing step in computer vision tasks,
groups pixels into perceptually coherence atomic regions to replace the pixel grid in images …