Deep learning (DL) has made breakthroughs in many computer vision tasks and also in
visual tracking. From the beginning of the research on the automatic acquisition of high …

Transformer has shown excellent performance in remote sensing field with long-range
modeling capabilities. Remote sensing video (RSV) moving object detection and tracking …

As a vital topic in media content interpretation, video anomaly detection (VAD) has made
fruitful progress via deep neural network (DNN). However, existing methods usually follow a …

Multi-person pose estimation and tracking serve as crucial steps for video understanding.
Most state-of-the-art approaches rely on first estimating poses in each frame and only then …

Modern online multiple object tracking (MOT) methods usually focus on two directions to
improve tracking performance. One is to predict new positions in an incoming frame based …

Abstract Multi-Camera Multi-Object Tracking (MC-MOT) utilizes information from multiple
views to better handle problems with occlusion and crowded scenes. Recently, the use of …

State-of-the-art multi-object tracking (MOT) methods follow the tracking-by-detection
paradigm, where object trajectories are obtained by associating per-frame outputs of object …

Online tracking of multiple objects in videos requires strong capacity of modeling and
matching object appearances. Previous methods for learning appearance embedding …

With rapid advancements in depth sensors and deep learning, skeleton-based person re-
identification (re-ID) models have recently achieved remarkable progress with many …

Abstract Multi-Camera Multi-Object Tracking is currently drawing attention in the computer
vision field due to its superior performance in real-world applications such as video …