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

As the GAN-based face image and video generation techniques, widely known as
DeepFakes, have become more and more matured and realistic, there comes a pressing …

Existing methods for Salient Object Detection in Optical Remote Sensing Images (ORSI-
SOD) mainly adopt Convolutional Neural Networks (CNNs) as the backbone, such as VGG …

Visual object tracking is an important task in computer vision, which has many real-world
applications, eg, video surveillance, visual navigation. Visual object tracking also has many …

Traditional color images only depict color intensities in red, green and blue channels, often
making object trackers fail in challenging scenarios, eg, background clutter and rapid …

Spatial boundary effect can significantly reduce the performance of a learned discriminative
correlation filter (DCF) model. A commonly used method to relieve this effect is to extract …

Tracking objects across multiple video frames is a challenging task due to several difficult
issues such as occlusions, background clutter, lighting as well as object and camera view …

Vision-based object tracking has boosted extensive autonomous applications for unmanned
aerial vehicles (UAVs). However, the dynamic changes in flight maneuver and viewpoint …

Spatial regularization has been proved as an effective method for alleviating the boundary
effect and boosting the performance of a discriminative correlation filter (DCF) in aerial …

Low light images captured in a non-uniform illumination environment usually are degraded
with the scene depth and the corresponding environment lights. This degradation results in …