Deep learning in video multi-object tracking: A survey

Deep Residual Learning for Image Recognition

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Support-Vector Networks

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Histograms of Oriented Gradients for Human Detection

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Utilization of Kine Master Application as a Learning Video

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Occluded vehicle tracking by integrating full-scale features and trajectory correction

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UniSORT: Tracking with unified cue integration and refined association

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Evaluating traffic trajectories from stationary multiple object tracking systems

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A Coordinated Interaction and Cross Enhancement Network for Salient Object Detection

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TrackOR: Towards Personalized Intelligent Operating Rooms Through Robust Tracking

Wang, T. D., Heiliger, C., Navab, N., & Bastian, L. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-09784-2_6 · Cited by 1

D-DeepOCSORT: multi-object tracking algorithm based on LiDAR and monocular camera

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Dissolving boundaries in the Metaverse: Implications of loosened constraints on identity, time, space, and financial access for marketing research

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A Comprehensive Review of Position and Movement Visual Monitoring Systems with an Emphasis on AI Methods

Filo, G., Lempa, P., & Wisowski, K. (2026) · Applied Sciences · doi:10.3390/app16094497 · Cited by 1

An automated dynamic adaptive tracking and counting method for grazing sheep based on UAV imagery and YOLO11-OBB

Zhang, X., Zhang, L., Lü, Y., Yang, F., Zhang, J., Jiang, X., Jiao, L., & Gong, M. (2026) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2026.112086 · Cited by 1

Occlusion handling algorithms in visual object tracking: a survey

Peker, K., & Altilar, D. T. (2026) · Applied Intelligence · doi:10.1007/s10489-026-07345-4 · Cited by 1

A Comparative Evaluation of Lightweight YOLO Detectors with BoT-SORT and ByteTrack for Real-Time Multi-Object Tracking

Pranata, F. S., Na’am, J., Yulhan, Lisna, Y. P., Utami, R. A., Rahmatunisa, R., Saputra, I., Putri, E. Y., Mahniza, M., & Hutasuhut, N. I. (2026) · International Research Journal of Multidisciplinary Scope · doi:10.47857/irjms.2026.v07i03.011543 · Cited by 1

Retrieval Augmented Continuous Person Tracking and Re-Identification

Sharma, M., Singh, A., Kunwar, A., Tagore, N. K., & Kumar, S. (2025) · Indian Conference on Computer Vision, Graphics and Image Processing · doi:10.1145/3774521.3774616 · Cited by 1

ReynoldsFlow: Physics-Inspired Spatiotemporal Flow Representation for Video Understanding

Chen, Y., Ching-Kai, L., Huang, P., & Wu, C.-T. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37422-6_31 · Cited by 1

Bridging the Gap between Semantics and Multimedia Processing

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DeepTracks: Geopositioning Maritime Vehicles in Video Acquired from a Moving Platform

Wei, J., Xu, G., & Yılmaz, A. (2021) · Proceedings of IEEE Sensors/Proceedings of IEEE Sensors ... · doi:10.1109/sensors47087.2021.9639595 · Cited by 1

Less false detections, fewer identity switches: methods for the improvement of deep sort

Huang, Z., Tan, K., & Wei, Z. (2021) · Seventh International Symposium on Precision Mechanical Measurements · doi:10.1117/12.2612162 · Cited by 1

Establishing trajectories of moving objects without identities: The intricacies of cell tracking and a solution

Cazzolato, M. T., Traina, A. J. M., & Böhm, K. (2021) · Information Systems · doi:10.1016/j.is.2021.101955 · Cited by 1

Network Video Frame-Skip Modeling and Simulation

Cempron, J. P. C., & Ilao, J. P. (2021) · International Conference on Mechatronics and Machine Vision in Practice (M2VIP) · doi:10.1109/m2vip49856.2021.9664996 · Cited by 1

Multi-Object Tracking Based on Deep Path Aggregation Network

Chen, X., & Zhang, Y. (2022) · International Conference on Image, Vision and Computing (ICIVC) · doi:10.1109/icivc55077.2022.9886718 · Cited by 1

Multi-object Tracking with Noisy Labels

Liu, W., Li, Y., Wang, J., Miao, Z., & Qiu, H. (2022) · International Conference on Pattern Recognition and Artificial Intelligence (PRAI) · doi:10.1109/prai55851.2022.9904177 · Cited by 1

Fast Multi-Object Tracking with Feature Pyramid and Region Proposal Networks

Vaquero, L., Brea, V. M., & Mucientes, M. (2022) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr56361.2022.9956673 · Cited by 1

M3T: Multi-class Multi-instance Multi-view Object Tracking for Embodied AI Tasks

Khan, M., Abu-Khalaf, J., Suter, D., & Rosenhahn, B. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-25825-1_18 · Cited by 1

Flotation Froth Monitoring Using Unsupervised Multiple Object Tracking Methods

Abrarov, A. (2023) · doi:10.54026/jmms/1054 · Cited by 1

Crowdsourcing System for Multi-object Annotation in Surveillance Videos

Zhang, Z., Zhao, Z., Zhang, L., & Li, X. (2022) · International Conference on Big Data Computing and Communications (BigCom) · doi:10.1109/bigcom57025.2022.00055 · Cited by 1

Observation Noise Covariance Matrix Initialization-Based Objective State Estimation for Kalman Filter Using SVR

Chen, J., Liu, M., Ren, F., Yuan, P., Chen, J., Ma, Y., Liu, T., & Piao, C. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-99-1252-0_10 · Cited by 1

Quadcopter Capable of Autonomously Chasing Micro-Aircraft with Real-Time Visual Tracker

Lee, D., Park, W., Yi, J., Byun, W., Huh, S., & Nam, W. (2023) · International Conference on Unmanned Aircraft Systems (ICUAS) · doi:10.1109/icuas57906.2023.10156489 · Cited by 1

X-Tracking: Tracking Human in Masking Surveillance Video

Wu, Z., Ke, W., Wang, C., & Xiong, Z. (2022) · International Conference on Universal Village (UV) · doi:10.1109/uv56588.2022.10185520 · Cited by 1

Deep Learning-based Cnn Multi-modal Camera Model Identification for Video Source Identification

Singh, S., & Sehgal, V. K. (2023) · Informatica · doi:10.31449/inf.v47i3.4392 · Cited by 1

Observation-Centric with Appearance Metric for Computer Vision-Based Vehicle Counting

Brillantes, A. K. M., Sybingco, E., Billones, R. K. C., Bandala, A. A., Fillone, A. M., & Dadios, E. P. (2023) · Journal of Advances in Information Technology · doi:10.12720/jait.14.6.1261-1272 · Cited by 1

Smart Junctions: Yolov5, DeepSORT, and Direction Analysis for Traffic Enhancement

Syed Abudhagir, U., Koushik, K., Reddy, K. V., & Goud, G. B. K. (2024) · International Conference on Trends in Engineering Systems and Technologies (ICTEST) · doi:10.1109/ictest60614.2024.10576081 · Cited by 1

Panoramic Multi-Target Tracking Model Incorporating Human Features and Motion Model

Shen, J., Yang, H., & Song, W. (2024) · International Conference on Computer Communication and Artificial Intelligence (CCAI) · doi:10.1109/ccai61966.2024.10603027 · Cited by 1

MixFEAN: Enhancing Multi-Object Tracking for Intelligent Sports Analysis through Conditional Feature Mixing and Dynamic Re-weighting

Zhang, Z., Pa, W. A. M. W., Zhang, C., Mazalan, N. S., & Liu, W. (2024) · International Conference on Robotics, Artificial Intelligence and Intelligent Control (RAIIC) · doi:10.1109/raiic61787.2024.10671229 · Cited by 1

Multi-Object Tracking With Separation in Deep Space

Hu, M., Wang, H., Wang, H., Li, B., Cao, S., Zhan, T., Zhu, X., Liu, T., Liu, C., & Song, Q. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3522290 · Cited by 1

MAML MOT: Multiple Object Tracking Based on Meta-Learning

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DEVELOPMENT OF AN ANNOTATED DATABASE FOR ASSESING THE PERFORMANCE OF DEEP LEARNING-BASED VEHICLE DETECTION AND TRACKING MODELS

Barbu, T., Bejinariu, S.-I., & Luca, R. (2024) · Annals of the Academy of Romanian Scientists Series on Science and Technology of Information · doi:10.56082/annalsarsciinfo.2024.2.22 · Cited by 1

Tracking and Computation of Characteristics of the Movement of People in Groups on Video Using Convolutional Neural Networks

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Research on Multi object Occlusion Tracking and Trajectory Prediction Method Based on Deep Reinforcement Learning

Yuan, T., & Fei, S. (2024) · International Conference on Robotics, Intelligent Control and Artificial Intelligence (RICAI) · doi:10.1109/ricai64321.2024.10911233 · Cited by 1

Video-based multi-target multi-camera tracking for postoperative phase recognition

Jurosch, F., Zeller, J., Wagner, L., Özsoy, E., Jell, A., Kolb, S., & Wilhelm, D. (2025) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-025-03344-x · Cited by 1

Modeling Score Distributions and Continuous Covariates: A Bayesian Approach

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FIOU Tracker: An Improved Algorithm of IOU Tracker in Video with a Lot of Background Inferences

Chen, Z., Qiu, G., Zhang, H., Sheng, B., & Li, P. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-61864-3_13 · Cited by 1

Small Ball Tracking with Trajectory Prediction

Ferede, S., Xie, X., Zhang, C. B. C., Du, J., & Shi, G. (2020) · IEEE International Conference on Signal and Image Processing (ICSIP) · doi:10.1109/icsip49896.2020.9339461 · Cited by 1

Tracking Livestock Using a Fully Connected Network and Kalman Filter

Sarwar, F., Griffin, A., & Pasang, T. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-72073-5_19 · Cited by 1

A CNN-based cell tracking method for multi-slice intravital imaging data

Fujimoto, K., Mizugaki, T., Rajkumar, U., Shigeta, H., Seno, S., Uchida, Y., Ishii, M., Bafna, V., & Matsuda, H. (2021) · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · doi:10.1145/3459930.3469559 · Cited by 1

End-to-End On-Line Multi-object Tracking on Sparse Point Clouds Using Recurrent Convolutional Networks

Spata, D., Grumpe, A., & Kummert, A. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86380-7_33 · Cited by 1

Pedestrian Tracking Algorithm Combining Contextual Information and Attention Mechanism

Xiao, S., Qiang, Z., Liu, W.-G., & Bao, X. (2021) · American Journal of Computer Science and Technology · doi:10.11648/j.ajcst.20210404.14 · Cited by 1

Intelligent Traffic Accident Detection System Using Surveillance Video

Sun, P., & Liu, Q. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-16-2090-4_61 · Cited by 1

TrichTrack: Multi-Object Tracking of Small-Scale Trichogramma Wasps

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Computer Vision-based Detection and Tracking in the Olive Sorting Pipeline

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Low Cost Player Tracking in Field Hockey

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Depth-Aware Multi-object Tracking in Spherical Videos

Presti, L. L., Mazzola, G., Averna, G., Ardizzone, E., & Cascia, M. L. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-06433-3_31 · Cited by 1

Route Planning for Autonomous Transmission of Large Sport Utility Vehicle

Vijayakumar, V., Shanthini, J., Karthik, S. S., & Srihari, K. (2022) · Computer Systems Science and Engineering · doi:10.32604/csse.2023.028400 · Cited by 1

Online Multi-Object Tracking Under Moving Unmanned Aerial Vehicle Platform Based on Object Detection and Feature Extraction Network

Liu, Z., Wang, S., Yao, L., & Cai, Y. (2022) · Journal of Shanghai Jiaotong University (Science) · doi:10.1007/s12204-022-2540-4 · Cited by 1

Backdoor Attack Against Deep Learning-Based Autonomous Driving with Fogging

Liu, J., Luo, L., & Wang, X. (2022) · Communications in computer and information science · doi:10.1007/978-981-19-7943-9_21 · Cited by 1

Towards Multi-Camera System for the Evaluation of Motorcycle Driving Test

Leone, G. R., Righi, M., Moroni, D., & Paolucci, F. (2022) · International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) · doi:10.1109/sitis57111.2022.00090 · Cited by 1

Neural Texture Puppeteer: A Framework for Neural Geometry and Texture Rendering of Articulated Shapes, Enabling Re-Identification at Interactive Speed

Waldmann, U., Johannsen, O., & Goldlüecke, B. (2024) · IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) · doi:10.1109/wacvw60836.2024.00016 · Cited by 1

Bidirectional Tracking Method for Construction Workers in Dealing with Identity Errors

Liu, Y., Wang, Y., & Zhou, Z. (2024) · Mathematics · doi:10.3390/math12081245 · Cited by 1

Psychophysical Evaluation of Deep Re-Identification ModelsPreprint

Nicholson, H. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.02136 · Cited by 1

Detecting estrus in sows using a robotic imaging system and neural networks

Xu, Z. (2023) · doi:10.32469/10355/97011 · Cited by 1

Pedestrian Trajectory Dataset of Public European Squares

Wolff, N., Perry, L., Venverloo, T., Slingerland, G., Wreyford, J. M., Santi, P., & Duarte, F. (2026) · Scientific Data · doi:10.1038/s41597-026-06686-6 · Cited by 1

Edge-Constrained Video Analytics: A Comprehensive Survey on Detection, Tracking, and Recognition

Toshpulatov, M. A., Lee, W., & Cho, J. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6614394

Appearance-free Tripartite Matching for Multiple Object TrackingPreprint

Wang, L., Zhu, Y., Shi, J., & Fan, X. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.03628

Multiple Objects Tracking with High-speed Multi-camera System

Iwakuma, K., & Yamakawa, Y. (2020) · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · doi:10.1299/jsmermd.2020.2p2-j15

Clique: Spatiotemporal Object Re-identification at the City ScalePreprint

Xu, T., Shen, K., Fu, Y. L., Shi, H., & Lin, F. X. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.09329

TagMe: GPS-Assisted Automatic Object Annotation in VideosPreprint

He, S., Bastani, F., Alizadeh, M., Balakrishnan, H., Cafarella, M., Kraska, T., & Madden, S. R. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.13428

Frame Rate Latency Reduction for Real-time Vehicle Tracking using Network Cameras

Cempron, J. P. C., Bautista, C. M., Cu, G., & Ilao, J. P. (2021) · IEEE Region 10 Symposium (TENSYMP) · doi:10.1109/tensymp52854.2021.9550916

Object Tracking in Video Using the TLD and CMT Fusion Model

Trần, H. (2021) · International Journal of Computer and Information Technology(2279-0764) · doi:10.24203/ijcit.v10i5.151

Approach to Define the Reliability of Safety-Related Machine Learning Based Functions in Highly Automated Driving

Si, P., Krini, O., Müller, N., & Ouertani, A. (2021) · Frontiers in artificial intelligence and applications · doi:10.3233/faia210427

Performance Improvement Method of the Video Visual Relation Detection with Multi-modal Feature Fusion

Kim, K., Kim, P.-K., Lim, K.-T., & Lee, J. T. (2022) · International Conference on Artificial Intelligence in Information and Communication (ICAIIC) · doi:10.1109/icaiic54071.2022.9722699

Graph Convolutional Network-based Centre-Object Tracking for the multi-dynamic agents for Autonomous Vehicles

Singh, D., & Srivastava, R. (2021) · International Conference on Information Systems and Computer Networks (ISCON) · doi:10.1109/iscon52037.2021.9702417

An Asynchronous Heterogeneous Fusion Framework for RF Localization Ensembles

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Multi-Object Tracking Algorithm Based on Improved FairMOT Feature Decoupling

刘, 文. (2022) · Computer Science and Application · doi:10.12677/csa.2022.128196

Unsupervised Multi-object Tracking via Dynamical VAE and Variational Inference

Lin, X. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548754

Dynamic Multi-ROI Parallel Inference Architecture for Online Video

Liu, T., Lu, X., Xue, D., Zhou, M., & Feng, R. (2022) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2022-01-7091

Defensive Bit Planes: Defense Against Adversarial Attacks

Tripathi, A. M., Behera, S. R., & Paul, K. (2022) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn55064.2022.9891957

Analysis on Chest X-ray and Computed Tomography Images to Detect COVID-19 Based on Deep Learning Techniques

Kanimozhi, J., Mohanasuganthi, N., Priyadharshini, A., Rohini, M. S., & Swathilakshmi, V. (2022) · International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI) · doi:10.1109/icdsaai55433.2022.10028873

On Formal Models of Interactions Between Detectors and Trackers in Crowd Analysis Tasks

Sluzek, A. S., & Zitouni, M. S. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-22025-8_2

Image Based Multi Objects' Trajectories Estimation through Reduced Order Observer

Raza, Y., Zia, A., Malik, M. B., Malik, F. M., Qayyum, A., & Malik, M. I. (2022) · International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) · doi:10.1109/macs56771.2022.10023115

SDSCF Tracker: An improved deep learning-based approach to execute target trackingPreprint

Gautam, A., & Singh, S. (2023) · Research Square · doi:10.21203/rs.3.rs-2395820/v1

Object Tracking for the Rotating Table Test

Scharf, V., Syed, I. S., Stolarz, M., Mehta, M., & Houben, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-28469-4_7

Detection of Moving Object Using Modified Fuzzy C-Means Clustering from the Complex and Non-stationary Background Scenes

Sangle, R., & Jetawat, A. K. (2023) · Springer proceedings in mathematics & statistics · doi:10.1007/978-3-031-16178-0_18

ADL: Anomaly Detection and Localization in Crowded Scenes Using Hybrid MethodsPreprint

Rui, B., & Wu, H. (2023) · Preprints.org · doi:10.20944/preprints202305.1617.v1

ADL: Anomaly Detection and Localization in Crowded Scenes Using Hybrid MethodsPreprint

Wu, H., Rui, B., & Li, L. (2023) · Preprints.org · doi:10.20944/preprints202305.1617.v3

Mixture of Dynamical Variational Autoencoders for Multi-Source Trajectory Modeling and SeparationPreprint

Lin, X., Laurent Girin, B., & Alameda-Pineda, X. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2312.04167

Object-oriented basis of artificial intelligence methodologies

Yeturu, K. (2023) · Handbook of statistics · doi:10.1016/bs.host.2023.06.001

Kompetenzzentrum für Roboter als Assistenz für Menschen mit Einschränkungen (OPERATE) - Förderkennzeichen 16SV8607

Dalm, K., Sahuji, R., Frank, F., & Ruhbach, L. (2023) · KIT Scientific Publishing eBooks · doi:10.58895/ksp/1000151552-8

Robust Environmental Perception of Multi-object Tracking

Pan, H., Wang, J., Yu, X., Sun, W., & Gao, H. (2023) · Recent advancements in connected autonomous vehicle technologies · doi:10.1007/978-981-99-7790-1_6

Looking with Machine Eyes: City Monitoring for Urban Resilience

Ceccarelli, G., Presicce, D., & Deponte, D. (2023) · Urban sustainability · doi:10.1007/978-981-99-7996-7_4

Three-dimensional shape estimation of wires from three-dimensional X-ray computed tomography images of electrical cables

Ueda, S., Sato, K., Saitô, H., & Hoshina, Y. (2024) · Journal of Electronic Imaging · doi:10.1117/1.jei.33.3.031209

A Real-Time Pedestrian Tracking Method Based on Enhanced Tracktor

Song, H., Li, J., Wan, F., & Hong, J. (2023) · International Conference on Electronic Information Technology and Computer Engineering (EITCE) · doi:10.1145/3650400.3650537

Digging Deeper With Machine Learning for Unbalanced Multimedia Data Categorization

Nihayatusyifa, N., & Febrianti, D. (2024) · Journal of Multimedia Trend and Technology. · doi:10.35671/jmtt.v3i1.47

UAV Farmland Object Tracking Based on Improved QDTrack

Li, Z., Yu, X., Wang, D., & Liu, X. (2024) · International Conference on Machine Learning and Computing (ICMLC) · doi:10.1145/3651671.3651727

Integrating similarity and interaction force between objects for multiple object tracking

Wang, K., Dai, F., Guo, W., Wang, J., & Wang, X. (2024) · Journal of Image and Graphics · doi:10.11834/jig.230340

Hierarchical Vs Centroid-Based Constraint Clustering for Animal Video Data

Hennessey, S. L., Williams, F. J., & Kuncheva, L. I. (2024) · IEEE International Conference on Intelligent Systems · doi:10.1109/is61756.2024.10705263

LFEMSFF: A Basketball Posture Detection Model Combining Local Feature Enhancement and Multi-Camera Spatio-Temporal Feature Fusion

Liu, W., Koh, D., Zhang, Z., & Qiu, J. (2024) · International Conference on Electronics and Communication, Network and Computer Technology (ECNCT) · doi:10.1109/ecnct63103.2024.10704235

Evaluating the Use of Edge Devices for Detection and Tracking of Vehicles in Smart City Environment

Kocejko, T., Neumann, T., Mazur-Milecka, M., Kowalczyk, N., Rumiński, J., Jo, K.-H., Kaszynski, M., & Ludwisiak, T. (2024) · International Workshop on Intelligent Systems (IWIS) · doi:10.1109/iwis62722.2024.10706028

Genetic Programming-Based Multi-Object Matching for Mussel Floats in Mussel Farm Images

Zeng, D., Bi, Y., Liu, I., Xue, B., Vennell, R., & Zhang, M. (2024) · International Conference on Image and Vision Computing New Zealand (IVCNZ) · doi:10.1109/ivcnz64857.2024.10794448

Efficient CNN-based Object ID Association Model for Multiple Object Tracking

Danesh, P., Amini, E., & Kusetoğulları, H. (2024) · International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) · doi:10.1109/iceccme62383.2024.10796883

Enhancing Target Tracking Capability in Weapon Systems Using Target Detection and Sensor Network Mechanisms

Liu, J., Qi, W., Hou, G., Lv, M., & Wang, Z. (2024) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2891/11/112017

TFS: Revisiting Temporal Language Grounding from Frequency Spiking Perspective

Lyu, Y., Wu, H., Liu, L., & Sun, C. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10889584

A Review of Multi‐Object Tracking in Recent Times

Li, S., Ren, H., Xie, X., & Cao, Y. (2025) · IET Computer Vision · doi:10.1049/cvi2.70010 · Cited by 44

A systematic survey on recent deep learning-based approaches to multi-object tracking

Agrawal, H., Halder, A., & Chattopadhyay, P. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16910-9 · Cited by 12

Approaches to Video Real time Multi-Object Tracking and Object Detection: A survey

Bouraya, S., & Belangour, A. (2021) · International symposium on image and signal processing and analysis/ISPA ... · doi:10.1109/ispa52656.2021.9552095 · Cited by 7

A Systematic Review of Multi-Object Tracking Using Deep Learning in Video SequencesPreprint

EL-HAWARY, H. M., Sayed, U., El-Zohny, M. A., Mohamed, M. S., Mahmoud, A., & Mahmoud, A. A. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6500531

Deep Learning-based Visual Multiple Object Tracking:A Review

WU Han, N. J. (2023) · DOAJ (DOAJ: Directory of Open Access Journals) · doi:10.11896/jsjkx.220300173