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 …

Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …

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

Recently, the Segment Anything Model (SAM) gains lots of attention rapidly due to its
impressive segmentation performance on images. Regarding its strong ability on image …

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 …

Anchor-based Siamese trackers have achieved remarkable advancements in accuracy, yet
the further improvement is restricted by the lagged tracking robustness. We find the …

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 …

Most of the existing trackers usually rely on either a multi-scale searching scheme or pre-
defined anchor boxes to accurately estimate the scale and aspect ratio of a target …

Visual tracking is fundamentally the problem of regressing the state of the target in each
video frame. While significant progress has been achieved, trackers are still prone to failures …

Visual tracking problem demands to efficiently perform robust classification and accurate
target state estimation over a given target at the same time. Former methods have proposed …