Image captioning is a research area of immense importance, aiming to generate natural language descriptions for visual content in the form of still images. The advent of deep learning and more recently vision-language pre-training techniques has ...

Underwater computer vision has attracted increasing attention in the research community due to the recent advances in underwater platforms such as of rovers, gliders, autonomous underwater vehicles (AUVs), and the like, that now make possible the ...

With the development of convolutional neural networks, hundreds of deep learning–based dehazing methods have been proposed. In this article, we provide a comprehensive survey on supervised, semi-supervised, and unsupervised single image dehazing. We first ...

Object pose detection and tracking has recently attracted increasing attention due to its wide applications in many areas, such as autonomous driving, robotics, and augmented reality. Among methods for object pose detection and tracking, deep learning is ...

Representing dynamic textures (DTs) plays an important role in many real implementations in the computer vision community. Due to the turbulent and non-directional motions of DTs along with the negative impacts of different factors (e.g., environmental ...

We present a literature review to analyze the state of the art in the area of road detection based upon frontal images. For this purpose, a systematic literature review (SLR) was conducted that focuses on analyzing region-based works, since they can ...

Deep learning has recently gained popularity achieving state-of-the-art performance in tasks involving text, sound, or image processing. Due to its outstanding performance, there have been efforts to apply it in more challenging scenarios, for example, ...

Integrating computer vision and natural language processing is a novel interdisciplinary field that has received a lot of attention recently. In this survey, we provide a comprehensive introduction of the integration of computer vision and natural ...

Target-tracking algorithms typically organize the network into a logical structure (e.g., tree, cluster, or faces) to enable data fusion and reduce communication costs. These algorithms often predict the target’s future position. In addition to using ...

Grammars are widely used to describe string languages such as programming and natural languages and, more recently, biosequences. Moreover, since the 1980s grammars have been used in computer vision and related areas. Some factors accountable for this ...

Object class detection, also known as category-level object detection, has become one of the most focused areas in computer vision in the new century. This article attempts to provide a comprehensive survey of the recent technical achievements in this ...

The development of wireless sensor networks, such as researchers Advanced Driver Assistance Systems (ADAS) requires the ability to analyze the road scene just like a human does. Road scene analysis is an essential, complex, and challenging task and it ...

Human activity recognition is an important area of computer vision research. Its applications include surveillance systems, patient monitoring systems, and a variety of systems that involve interactions between persons and electronic devices such as ...

Although sensor planning in computer vision has been a subject of research for over two decades, a vast majority of the research seems to concentrate on two particular applications in a rather limited context of laboratory and industrial workbenches, ...

The distance transform (DT) is a general operator forming the basis of many methods in computer vision and geometry, with great potential for practical applications. However, all the optimal algorithms for the computation of the exact Euclidean DT (EDT) ...

The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to ...

Vessel segmentation algorithms are the critical components of circulatory blood vessel analysis systems. We present a survey of vessel extraction techniques and algorithms. We put the various vessel extraction approaches and techniques in perspective by ...

Two-dimensional image motion is the projection of the three-dimensional motion of objects, relative to a visual sensor, onto its image plane. Sequences of time-orderedimages allow the estimation of projected two-dimensional image motion as either ...