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) …

Transformer trackers have achieved impressive advancements recently, where the attention
mechanism plays an important role. However, the independent correlation computation in …

We present ARTrack, an autoregressive framework for visual object tracking. ARTrack
tackles tracking as a coordinate sequence interpretation task that estimates object …

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 …

With the popularity of multi-modal sensors, visible-thermal (RGB-T) object tracking is to
achieve robust performance and wider application scenarios with the guidance of objects' …

Transformer has shown excellent performance in remote sensing field with long-range
modeling capabilities. Remote sensing video (RSV) moving object detection and tracking …

Previous advances in object tracking mostly reported on favorable illumination
circumstances while neglecting performance at nighttime, which significantly impeded the …

Recently, the Siamese-based method has stood out from multitudinous tracking methods
owing to its state-of-the-art (SOTA) performance. Nevertheless, due to various special …

Recent object tracking methods depend upon deep networks or convoluted architectures.
Most of those trackers can hardly meet real-time processing requirements on mobile …

Visual tracking has made significant improvements in the past few decades. Most existing
state-of-the-art trackers 1) merely aim for performance in ideal conditions while overlooking …