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 …

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 …

Correlation acts as a critical role in the tracking field, especially in recent popular Siamese-
based trackers. The correlation operation is a simple fusion manner to consider the similarity …

In this paper, we present a new tracking architecture with an encoder-decoder transformer
as the key component. The encoder models the global spatio-temporal feature …

In video object tracking, there exist rich temporal contexts among successive frames, which
have been largely overlooked in existing trackers. In this work, we bridge the individual …

In this paper, we present a new sequence-to-sequence learning framework for visual
tracking, dubbed SeqTrack. It casts visual tracking as a sequence generation problem …

Optimization based tracking methods have been widely successful by integrating a target
model prediction module, providing effective global reasoning by minimizing an objective …

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) …

Recently Transformer has been largely explored in tracking and shown state-of-the-art
(SOTA) performance. However, existing efforts mainly focus on fusing and enhancing …

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