SCGTracker: object feature embedding enhancement based on graph attention networks for multi-object tracking
Xin Feng,
Xiaoning Jiao,
Siping Wang
et al.
Abstract:Multi-object tracking (MOT) is a task to identify objects in videos, however, objects with similar appearance or occlusion may cause frequent ID switching, which is the main challenge of current MOT. In this paper, we propose a novel self-cross graph neural network-based multi-object tracking method, which we termed as SCGTracker. This method seamlessly integrates object detection and tracking through graph neural networks, building upon the foundation of the JDE paradigm. Specifically, we construct graph stru… Show more
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