In this paper, we propose a CNN-based framework for online MOT. This framework utilizes
the merits of single object trackers in adapting appearance models and searching for target …

Abstract Recent Multiple Object Tracking (MOT) methods have gradually attempted to
integrate object detection and instance re-identification (Re-ID) into a united network to form …

Multi-object tracking is a significant domain in Computer vision applications, which involves
giving unique identities to different objects, and maintaining the association between them …

Modern multi-object tracking (MOT) benefited from recent advances in deep neural network
and large video datasets. However, there are still some challenges impeding further …

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 …

The recent trend in vision-based multi-object tracking (MOT) is heading towards leveraging
the representational power of deep learning to jointly learn to detect and track objects …

Over the past few years, unmanned aerial vehicles (UAVs) or drones have been deployed
across the military services. At the same time, the civilian market has seen an exponential …

Multi-object tracking is a significant field in computer vision since it provides essential
information for video surveillance and analysis. Several different deep learning-based …

The capability of the unmanned aerial vehicle (UAV) to capture highly informative data has
expanded its utility in multiple sectors. Surveillance-based UAV applications have highly …

Abstract The Deep Learning techniques has proven its effectiveness in so many computer
vision (CV) tasks and one of those are the multi object detection and multi object tracking …