Single object tracking (SOT) in satellite video (SV) enables the continuous acquisition of
position and range information of an arbitrary object, showing promising value in remote …

Thermal infrared (TIR) target tracking task is not affected by illumination changes and can be
tracked at night, on rainy days, foggy days, and other extreme weather; so it is widely used in …

Tracking often uses a multi-stage pipeline of feature extraction, target information
integration, and bounding box estimation. To simplify this pipeline and unify the process of …

Object modeling has become a core part of recent tracking frameworks. Current popular
tackers use Transformer attention to extract the template feature separately or interactively …

Temporal contexts among consecutive frames are far from being fully utilized in existing
visual trackers. In this work, we present TCTrack, a comprehensive framework to fully exploit …

Owing to effective and flexible data acquisition, unmanned aerial vehicles (UAVs) have
recently become a hotspot across the fields of computer vision (CV) and remote sensing …

Siamese network based trackers formulate the visual tracking task as a similarity matching
problem. Almost all popular Siamese trackers realize the similarity learning via convolutional …

By decomposing the visual tracking task into two subproblems as classification for pixel
category and regression for object bounding box at this pixel, we propose a novel fully …

Drones, or general UAVs, equipped with cameras have been fast deployed with a wide
range of applications, including agriculture, aerial photography, and surveillance …

Most existing trackers based on discriminative correlation filters (DCF) try to introduce
predefined regularization term to improve the learning of target objects, eg, by suppressing …