Multi-object tracking (MOT) is mainly used for detecting and tracking the object on multi-
cameras, which is widely applied in intelligent video surveillance and intelligent security …

In recent years, computer vision applications based on deep learning have developed
rapidly, and systems such as smart buildings, smart cities and surveillance and security …

Multi-object tracking (MOT) is pivotal for under-standing environments in which unmanned
vehicles function. The Joint Detection and Embedding (JDE) paradigm, merging target …

Characterized by the ability to handle varying number of objects, tracking by detection
framework becomes increasingly popular in multiobject tracking (MOT) problem. However …

In this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-
resolution aerial imagery by intensive evaluation of a number of traditional and Deep …

Object tracking has gained importance in various applications especially in traffic
monitoring, surveillance and security, people tracking, etc. Previous methods of multiobject …

The intelligent vehicle driverless technology has become a very hot topic in the past two
decades. To solve the road safety problem, the multi-target tracking system has attracted …

Objective of multiple object tracking (MOT) is to assign a unique track identity for all the
objects of interest in a video, across the whole sequence. Tracking-by-detection is the most …

Object tracking has emerged as an essential process for various applications in the field of
computer vision, such as autonomous driving. Recently, object tracking technology has …

In multi-object tracking, this paper proposes a multi-object tracking algorithm based on
improved TrackFormer, aiming at the problem that the tracking object is occluded or partially …