Visual target tracking is one of the most sought-after yet challenging research topics in
computer vision. Given the ill-posed nature of the problem and its popularity in a broad …

Recently, deep learning has achieved great success in visual tracking. The goal of this
paper is to review the state-of-the-art tracking methods based on deep learning. First, we …

Tracking in the unmanned aerial vehicle (UAV) scenarios is one of the main components of
target-tracking tasks. Different from the target-tracking task in the general scenarios, the …

The training of a feature extraction network typically requires abundant manually annotated
training samples, making this a time-consuming and costly process. Accordingly, we …

The fully-convolutional siamese network based on template matching has shown great
potentials in visual tracking. During testing, the template is fixed with the initial target feature …

With the advantage of high mobility, Unmanned Aerial Vehicles (UAVs) are used to fuel
numerous important applications in computer vision, delivering more efficiency and …

Observing that Semantic features learned in an image classification task and Appearance
features learned in a similarity matching task complement each other, we build a twofold …

Abstract Deep Neural Networks (DNNs) have substantially improved the state-of-the-art in
salient object detection. However, training DNNs requires costly pixel-level annotations. In …

How to effectively learn temporal variation of target appearance, to exclude the interference
of cluttered background, while maintaining real-time response, is an essential problem of …

Abstract Correlation Filters (CFs) have recently demonstrated excellent performance in
terms of rapidly tracking objects under challenging photometric and geometric variations …