Kalman filter (KF) based methods for multi-object tracking (MOT) make an assumption that
objects move linearly. While this assumption is acceptable for very short periods of …

Online action detection in surveillance scenarios presents considerable challenges,
particularly due to the dynamically changing environments and real-time processing …

Digital aquaculture leverages advanced technologies and data-driven methods, providing
substantial benefits over traditional aquaculture practices. This paper presents a …

The field of AI agents is advancing at an unprecedented rate due to the capabilities of large
language models (LLMs). However, LLM-driven visual agents mainly focus on solving tasks …

Non-invasive methods of fish counting are crucial for the effective management of
aquaculture and aquatic resources. However, accurate and reliable estimation of fish …

Accurate tool tracking is essential for the success of computer-assisted intervention.
Previous efforts often modeled tool trajectories rigidly, overlooking the dynamic nature of …

Current multi-object tracking (MOT) aims to predict trajectories of targets (ie,“where”) in
videos. Yet, knowing merely “where” is insufficient in many crucial applications. In …

In this paper we study multi-label atomic activity recognition. Despite the notable progress in
action recognition it is still challenging to recognize atomic activities due to a deficiency in …

Referring multi-object tracking (RMOT) aims to track multiple objects based on input textual
descriptions. Previous works realize it by simply integrating an extra textual module into the …

The complex dynamicity of open-world objects presents non-negligible challenges for multi-
object tracking (MOT) often manifested as severe deformations fast motion and occlusions …