12 datasets found

A lettuce MOTS dataset for tracking and segmentation of vegetable plants for robotic precision spray application in agriculture.

The UA-Detrac and UrbanTracker datasets were used for the evaluation in this study because they include four challenging real-world traffic videos with 4 to 20 targets in the...

The dataset used for the MOT20 challenge, which consists of 8 different sequences depicting very crowded challenging scenes.

MOT16 is a benchmark for multi-object tracking, consisting of 16 video sequences with 1000 frames each.

The VisDrone-MOT dataset is a large-scale benchmark for multiple object tracking under drone scenes.

Urban Tracker dataset for multiple object tracking in urban mixed traffic

The TAO MOT dataset is a large-scale benchmark for tracking any object.

The dataset used in the paper is a large collection of raw images from diverse domains, which are used to train a universal tracking adapter.

The CLEAR MOT metrics are used to evaluate the performance of multi-object tracking algorithms.

Unsupervised multiple-object tracking with a dynamical variational autoencoder

The proposed architecture is described in Fig. 3 which is based on TransTrack [21] with several improvements to reduce the computational complexity and model size.

Many Multi-Object Tracking (MOT) approaches exploit motion information to associate all the detected objects across frames. However, many methods that rely on filtering-based...