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Found 4 papers, 1 papers with code
Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector
Multiple object tracking (MOT) in urban traffic aims to produce the trajectories of the different road users that move across the field of view with different directions and speeds and that can have varying appearances and sizes.
Tracking in Urban Traffic Scenes from Background Subtraction and Object Detection
In this paper, we propose to combine detections from background subtraction and from a multiclass object detector for multiple object tracking (MOT) in urban traffic scenes.
Supervised and Unsupervised Detections for Multiple Object Tracking in Traffic Scenes: A Comparative Study
In this paper, we propose a multiple object tracker, called MF-Tracker, that integrates multiple classical features (spatial distances and colours) and modern features (detection labels and re-identification features) in its tracking framework.
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model
Recent breakthroughs in large language models (LLMs) have centered around a handful of data-rich languages.
