Recently, combining multiple features into discriminative correlation filters to improve
tracking representation has shown great potential in object tracking. Existing trackers apply …

Being intensively studied, visual tracking has seen great recent advances in either speed
(eg, with correlation filters) or accuracy (eg, with deep features). Real-time and high …

Convolutional neural network (CNN) has drawn increasing interest in visual tracking owing
to its powerfulness in feature extraction. Most existing CNN-based trackers treat tracking as …

Recently, the discriminative correlation filters (DCF)-based methods have performed
excellent precision and speed in object tracking. Due to the continuous change and …

Recent years have witnessed the top performances of integrating multi-level features from
the pre-trained convolutional neural network (CNN) into correlation filters framework …

In this paper, we propose a RGB-D tracking algorithm, built upon hierarchical multi-modal
fusion fully convolutional neural network (FCN) with attention model. First, we encode the …

Object tracking is considered a critical process in most applications of computer vision.
Recently, tracking algorithms that include correlation filter in their frameworks have gained …

Correlation filter has drawn increasing interest in visual tracking due to its high efficiency,
however, it is sensitive to partial occlusion, which may result in tracking failure. To address …

Visual object tracking has played a crucial role in computer vision with many applications.
Being intensively studied in recent decades, visual tracking has witnessed great advances …

Grayscale-thermal tracking has attracted a great deal of attention due to its capability of
fusing two different yet complementary target observations. Existing methods often consider …