In recent years, visual object tracking has become a very active research area. An
increasing number of tracking algorithms are being proposed each year. It is because …

We introduce CoTracker, a transformer-based model that tracks a large number of 2D points
in long video sequences. Differently from most existing approaches that track points …

Accurate and robust visual object tracking is one of the most challenging and fundamental
computer vision problems. It entails estimating the trajectory of the target in an image …

The tracking-by-detection framework consists of two stages, ie, drawing samples around the
target object in the first stage and classifying each sample as the target object or as …

Tracking by siamese networks has achieved favorable performance in recent years.
However, most of existing siamese methods do not take full advantage of spatial-temporal …

Structured output support vector machine (SVM) based tracking algorithms have shown
favorable performance recently. Nonetheless, the time-consuming candidate sampling and …

Discriminative correlation filters (DCFs) have\ryn been shown to perform superiorly in visual
tracking. They\ryn only need a small set of training samples from the initial frame to generate …

The state-of-the-art performance for object detection has been significantly improved over
the past two years. Besides the introduction of powerful deep neural networks, such as …

Recently, both correlation filters-based and Siamese-based trackers have achieved great
progress in the field of visual object tracking. Whereas, some trackers perform not that well …

In this paper, we propose a multi-task correlation particle filter (MCPF) for robust visual
tracking. We first present the multi-task correlation filter (MCF) that takes the …