In recent years, correlation filter-based (CF) tracking algorithms have gained momentum in
the field of visual tracking. CF tracking algorithms have achieved compelling performance by …

Occluded person re-identification (Re-ID) is a challenging task as persons are frequently
occluded by various obstacles or other persons, especially in the crowd scenario. To …

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 …

RGB-Infrared (IR) person re-identification is an important and challenging task due to large
cross-modality variations between RGB and IR images. Most conventional approaches aim …

Abstract Convolutional Neural Network (CNN) based methods generally take crowd
counting as a regression task by outputting crowd densities. They learn the map** …

Abstract The Visual Object Tracking challenge VOT2018 is the sixth annual tracker
benchmarking activity organized by the VOT initiative. Results of over eighty trackers are …

Siamese approaches address the visual tracking problem by extracting an appearance
template from the current frame, which is used to localize the target in the next frame. In …

Few-shot learning brings the machine close to human thinking which enables fast learning
with limited samples. Recent work considers local features to achieve contextual semantic …

Long-term visual tracking has drawn increasing attention because it is much closer to
practical applications than short-term tracking. Most top-ranked long-term trackers adopt the …

The fully-convolutional siamese network based on template matching has shown great
potentials in visual tracking. During testing, the template is fixed with the initial target feature …