Recently, Multi-Object Tracking (MOT) has attracted rising attention, and accordingly,
remarkable progresses have been achieved. However, the existing methods tend to use …

The nascent applicability of multi-camera tracking (MCT) in numerous real-world
applications makes it a significant computer vision problem. While visual tracking of objects …

Abstract Existing Multiple-Object Tracking (MOT) methods either follow the tracking-by-
detection paradigm to conduct object detection, feature extraction and data association …

We present a novel transformer-based architecture for global multi-object tracking. Our
network takes a short sequence of frames as input and produces global trajectories for all …

Due to balanced accuracy and speed, one-shot models which jointly learn detection and
identification embeddings, have drawn great attention in multi-object tracking (MOT) …

Abstract 3D multi-object tracking (MOT) has witnessed numerous novel benchmarks and
approaches in recent years, especially those under the “tracking-by-detection” paradigm …

Abstract The AI City Challenge's seventh edition emphasizes two domains at the intersection
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …

Multi-pedestrian trackers perform well when targets are clearly visible making the
association task quite easy. However, when heavy occlusions are present, a mechanism to …

Multi-object tracking (MOT) aims to associate target objects across video frames in order to
obtain entire moving trajectories. With the advancement of deep neural networks and the …

In recent years, algorithms for multiple object tracking tasks have benefited from great
progresses in deep models and video quality. However, in challenging scenarios like drone …