Structural health monitoring at local and global levels using computer vision technologies
has gained much attention in the structural health monitoring community in research and …

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 …

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

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 …

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

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 …

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 …

Transformer architecture has been showing its great strength in visual object tracking, for its
effective attention mechanism. Existing transformer-based approaches adopt the pixel-to …

The presence of objects that are confusingly similar to the tracked target, poses a
fundamental challenge in appearance-based visual tracking. Such distractor objects are …