Multi-object tracking is a fundamental vision problem that has been studied for a long time.
As deep learning brings excellent performances to object detection algorithms, Tracking by …

Driven by recent advances in object detection with deep neural networks, the tracking-by-
detection paradigm has gained increasing prevalence in the research community of multi …

In the same vein of discriminative one-shot learning, Siamese networks allow recognizing
an object from a single exemplar with the same class label. However, they do not take …

Due to better video quality and higher frame rate, the performance of multiple object tracking
issues has been greatly improved in recent years. However, in real application scenarios …

Recent progress in multiple object tracking (MOT) has shown that a robust similarity score is
a key to the success of trackers. A good similarity score is expected to reflect multiple cues …

In existing joint detection and tracking methods, pairwise relational features are used to
match previous tracklets to current detections. However, the features may not be …

Collaborative Robotics is one of the high-interest research topics in the area of academia
and industry. It has been progressively utilized in numerous applications, particularly in …

Abstract Multi-Target Tracking Guidance (MTTG) in unknown environments has great
potential values in applications for Unmanned Aerial Vehicle (UAV) swarms. Although Multi …

Multi-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science
mission, modern warfare surveillance, and disaster rescuing. This paper proposes a …

Multi-agent cooperative target tracking plays a significant role in distributed artificial
intelligence for unmanned aerial vehicle (UAV) systems. Most existing tracking solutions …