Multiple Object Tracking
114 papers with code • 8 benchmarks • 16 datasets
Multiple Object Tracking is the problem of automatically identifying multiple objects in a video and representing them as a set of trajectories with high accuracy.
Source: SOT for MOT
Benchmarks
These leaderboards are used to track progress in Multiple Object Tracking
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Libraries
Use these libraries to find Multiple Object Tracking models and implementationsDatasets
KITTI
Waymo Open Dataset
BDD100K
MOTChallenge
UA-DETRAC
KITTI MOTS
RADIATE
HiEve
SportsMOT
LPW
Latest papers
BoostTrack: boosting the similarity measure and detection confidence for improved multiple object tracking
To utilize low-detection score bounding boxes in one-stage association, we propose to boost the confidence scores of two groups of detections: the detections we assume to correspond to the existing tracked object, and the detections we assume to correspond to a previously undetected object.
Multiple Object Tracking as ID Prediction
MCG-NJU/MOTIP
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In Multiple Object Tracking (MOT), tracking-by-detection methods have stood the test for a long time, which split the process into two parts according to the definition: object detection and association.
PNAS-MOT: Multi-Modal Object Tracking with Pareto Neural Architecture Search
Multiple object tracking is a critical task in autonomous driving.
Delving into the Trajectory Long-tail Distribution for Muti-object Tracking
chen-si-jia/Trajectory-Long-tail-Distribution-for-MOT
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In this study, we pioneer an exploration into the distribution patterns of tracking data and identify a pronounced long-tail distribution issue within existing MOT datasets.
UCMCTrack: Multi-Object Tracking with Uniform Camera Motion Compensation
corfyi/ucmctrack
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In response to this, we introduce UCMCTrack, a novel motion model-based tracker robust to camera movements.
Adaptive Confidence Threshold for ByteTrack in Multi-Object Tracking
ByteTrack, a simple tracking algorithm, enables the simultaneous tracking of multiple objects by strategically incorporating detections with a low confidence threshold.
Multiple Toddler Tracking in Indoor Videos
ostadabbas/multiple-toddler-tracking
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Multiple toddler tracking (MTT) involves identifying and differentiating toddlers in video footage.
COOLer: Class-Incremental Learning for Appearance-Based Multiple Object Tracking
Continual learning allows a model to learn multiple tasks sequentially while retaining the old knowledge without the training data of the preceding tasks.
DARTH: Holistic Test-time Adaptation for Multiple Object Tracking
However, the nature of a MOT system is manifold - requiring object detection and instance association - and adapting all its components is non-trivial.
RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud
Mobile autonomy relies on the precise perception of dynamic environments.
