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Next Generation Multitarget Trackers: Random Finite Set Methods vs
  Transformer-based Deep Learning
v1v2v3 (latest)

Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning

1 April 2021
Juliano Pinto
Georg Hess
William Ljungbergh
Yuxuan Xia
Lennart Svensson
H. Wymeersch
ArXiv (abs)PDFHTMLGithub (42★)

Papers citing "Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning"

4 / 4 papers shown
Title
Transformer-Based Multi-Object Smoothing with Decoupled Data Association
  and Smoothing
Transformer-Based Multi-Object Smoothing with Decoupled Data Association and Smoothing
Juliano Pinto
Georg Hess
Yuxuan Xia
H. Wymeersch
Lennart Svensson
VOT
64
4
0
22 Dec 2023
Multi-Target Tracking with Transferable Convolutional Neural Networks
Multi-Target Tracking with Transferable Convolutional Neural Networks
Damian Owerko
Charilaos I. Kanatsoulis
Jennifer Bondarchuk
Donald J. Bucci
Alejandro Ribeiro
VOT
59
3
0
27 Oct 2022
Deep Fusion of Multi-Object Densities Using Transformer
Deep Fusion of Multi-Object Densities Using Transformer
Lechi Li
Chen Dai
Yuxuan Xia
Lennart Svensson
59
3
0
19 Sep 2022
Can Deep Learning be Applied to Model-Based Multi-Object Tracking?
Can Deep Learning be Applied to Model-Based Multi-Object Tracking?
Juliano Pinto
Georg Hess
William Ljungbergh
Yuxuan Xia
H. Wymeersch
Lennart Svensson
VOT
74
11
0
16 Feb 2022
1