Cited by 677Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and SafetyAdvanced Neural Network Applications

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Deep learning in video multi-object tracking: A survey

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Ciaparrone, Gioele, Luque Sánchez, Francisco, Tabik, Siham, Troiano, Luigi, Tagliaferri, Roberto, Herrera, Francisco·2020·Neurocomputing

DOI 10.1016/j.neucom.2019.11.023

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Authors: Ciaparrone, G., Luque Sánchez, F., Tabik, S., Troiano, L., Tagliaferri, R., & Herrera, F.
Affiliations: University of Salerno (IT)
Universidad de Granada (ES)
University of Sannio (IT)
Corresponding author: Ciaparrone, Gioele
ORCID: Ciaparrone, Gioele
Luque Sánchez, Francisco
Tabik, Siham
Troiano, Luigi
Tagliaferri, Roberto
Herrera, Francisco
Venue: Neurocomputing
Publisher: Elsevier BV
Published: 2020-03
Volume: 381
Pages: 61-88
ISSN: 0925-2312 (ISSN-L)
DOI: 10.1016/j.neucom.2019.11.023
OpenAlex: W2966535964
Cited by: 665
References: 199
Citations by year: 2026: 56 · 2025: 79 · 2024: 97 · 2023: 115 · 2022: 131 · 2021: 128 · 2020: 57
FWCI: 35.60
Type: journal article
Language: en
Open access: green
arxiv.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Neurocomputing (publishedVersion)
arXiv (Cornell University) (submittedVersion)
arXiv (Cornell University)
Funders: Fundación BBVA
Agencia Estatal de Investigación
Ministerio de Ciencia y Tecnología
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
Keywords: multi-target tracking, video tracking, deep learning, single-camera video, trajectory prediction, object detection

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