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 …

Unmanned aerial vehicle (UAV)-based visual object tracking has enabled a wide range of
applications and attracted increasing attention in the field of artificial intelligence (AI) …

Most of the existing trackers usually rely on either a multi-scale searching scheme or pre-
defined anchor boxes to accurately estimate the scale and aspect ratio of a target …

Abstract We present Siam R-CNN, a Siamese re-detection architecture which unleashes the
full power of two-stage object detection approaches for visual object tracking. We combine …

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

Siamese networks have drawn great attention in visual tracking because of their balanced
accuracy and speed. However, the backbone networks used in Siamese trackers are …

While recent years have witnessed astonishing improvements in visual tracking robustness,
the advancements in tracking accuracy have been limited. As the focus has been directed …

In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object
Tracking. LaSOT consists of 1,400 sequences with more than 3.5 M frames in total. Each …

Current state-of-the-art trackers rely only on a target appearance model in order to localize
the object in each frame. Such approaches are however prone to fail in case of eg fast …

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 …