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ROMOT: Referring-expression-comprehension open-set multi-object tracking
Traditional multi-object tracking is limited to tracking a predefined set of categories, whereas open-vocabulary tracking expands its capabilities to...
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Multi-object tracking: a systematic literature review
The field of computer vision is revolutionized with the advancement of deep learning and the availability of high computational power. In addition,...
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Adaptive multi-object tracking algorithm based on split trajectory
Multi-object tracking (MOT) has wide-ranging applications in unmanned vehicles, military reconnaissance, and video surveillance. However, real-world...
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Joint Detection and Association for End-to-End Multi-object Tracking
Multi-object tracking (MOT) is mainly used for detecting and tracking the object on multi-cameras, which is widely applied in intelligent video...
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TMTB: Transformer based multi-task branching multi-object tracking algorithm for wide-view scenes
Combining Unmanned aerial vehicle (UAV) with artificial intelligence can effectively extract information as UAV fly flexibly and have a wide view,...
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Multi-sensor fusion for real-time object tracking
Accurate orientation and position estimation are critical elements in optimizing real-time object tracking performance when leveraging smartphone...
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A robust deep networks based multi-object multi-camera tracking system for city scale traffic
Vision sensors are becoming more important in Intelligent Transportation Systems (ITS) for traffic monitoring, management, and optimization as the...
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MLGT: multi-local guided tracker for visual object tracking
Existing single-stream tracking pipelines achieve good performance improvements by joint feature extraction and interaction. These tracking pipelines...
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Towards Frame Rate Agnostic Multi-object Tracking
Multi-object Tracking (MOT) is one of the most fundamental computer vision tasks that contributes to various video analysis applications. Despite the...
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DIVOTrack: A Novel Dataset and Baseline Method for Cross-View Multi-Object Tracking in DIVerse Open Scenes
Cross-view multi-object tracking aims to link objects between frames and camera views with substantial overlaps. Although cross-view multi-object...
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Multi-object tracking using context-sensitive enhancement via feature fusion
Multi-object tracking (MOT) is one of the most challenging tasks in the field of computer vision. Most MOT methods generally face the problem of not...
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Unsupervised RGB-T object tracking with attentional multi-modal feature fusion
RGB-T tracking means that given the object position in the first frame, the tracker is trained to predict the position of the object in consecutive...
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UMTSS: a unifocal motion tracking surveillance system for multi-object tracking in videos
Multiple object detection and tracking play a very crucial role in solving several elementary problems in real-time surveillance video analysis and...
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Multi-cue multi-hypothesis tracking with re-identification for multi-object tracking
Multi-object tracking is an important research topic in the field of computer vision. In multi-object tracking, overlap** targets and dramatic...
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Multi-sensor based object tracking using enhanced particle swarm optimized multi-cue granular fusion
In the discipline of computer vision, object tracking is one of the progressive and prominent areas of research with its application in the field of...
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Implementation of an improved multi-object detection, tracking, and counting for autonomous driving
Autonomous vehicles are a family of complex systems permanently connected to the rest of the world and communicating autonomously with other systems....
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Adaptive Kalman Filter with power transformation for online multi-object tracking
By introducing a low-score detection box association stage, the full-detection association can effectively enhance the accuracy and robustness of...
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SiamMaskAttn: inverted residual attention block fusing multi-scale feature information for multitask visual object tracking networks
Multitask learning combining visual object tracking and other computer vision tasks has received increasing attention from researchers. Among them,...
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STMT: Spatio-temporal memory transformer for multi-object tracking
Typically, modern online Multi-Object Tracking (MOT) methods first obtain the detected objects in each frame and then establish associations between...
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GTAN: graph-based tracklet association network for multi-object tracking
Multi-object tracking (MOT) is a thriving research field in computer vision. The tracklet-based MOT frameworks are frequently employed to generate...
