Studies show lots of advanced research on various data types such as image, speech, and
text using deep learning techniques, but nowadays, research on video processing is also an …

With the widespread use of deep learning in single object tracking task, mainstream tracking
algorithms treat tracking as a combined classification and regression problem. Classification …

Recently, deep learning has achieved great success in visual tracking tasks, particularly in
single-object tracking. This paper provides a comprehensive review of state-of-the-art single …

Siamese tracking has witnessed tremendous progress in tracking paradigm. However, its
default box estimation pipeline still faces a crucial inconsistency issue, namely, the …

Siamese trackers have emerged as the predominant paradigm in visual tracking owing to
their robust similarity matching. However, relying on dense regression strategies for …

Recently, object tracking have achieved remarkable progress in terms of both efficiency and
accuracy. However, exiting methods still cannot satisfy challenging tasks under complicated …

Recently, spiking neural networks (SNNs), the third generation of neural networks, have
shown remarkable capabilities of energy-efficient computing, which is a promising …

Integrating multi-feature based on multi-layer features from the convolutional network or
based on multiple hand-crafted features has been proved to be an effective way for …

With the rapid advancement of deep learning, this technique has also shown promise in
single-object tracking, considerably enhancing the algorithm's performance. This paper will …

The increasing popularity of mobile applications has catalyzed advancements in object
tracking algorithms for mobile platforms. This paper introduces a lightweight object tracking …