In this paper, we propose a sequence-to-sequence affinity metric for the data association of
near-online multi-object tracking. The proposed metric learns the affinity between track …

In this work, we present an end-to-end framework to settle data association in online Multiple-
Object Tracking (MOT). Given detection responses, we formulate the frame-by-frame data …

In the last few years, enormous strides have been made for object detection and data
association, which are vital subtasks for one-stage online multi-object tracking (MOT) …

In this paper, we propose an online multi-object tracking (MOT) approach that integrates
data association and single object tracking (SOT) with a unified convolutional network …

Online multi-object tracking (MOT) is a longstanding task for computer vision and intelligent
vehicle platform. At present, the main paradigm is tracking-by-detection, and the main …

Abstract Online two-dimensional (2D) multi-object tracking (MOT) is a challenging task when
the objects of interest have similar appearances. In that case, the motion of objects is …

Abstract Appearance-based Multi-Object Tracking (MOT) methods rely on the appearance
cues of objects. However, existing deep appearance extraction schemes struggle to balance …

Abstract The majority of Multi-Object Tracking (MOT) algorithms based on the tracking-by-
detection scheme do not use higher order dependencies among objects or tracklets, which …

Most modern multi‐object tracking (MOT) systems for videos follow the tracking‐by‐
detection paradigm, where objects of interest are first located in each frame then associated …

Driven by recent advances in object detection with deep neural networks, the tracking-by-
detection paradigm has gained increasing prevalence in the research community of multi …