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Deep Learning in Video Multi-Object Tracking: A Survey

arXiv 1907.12740 ↗First posted 18 Jul 2019cs.CV cs.LG stat.MLcited by 107

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Abstract (arXiv)

The problem of Multiple Object Tracking (MOT) consists in following the trajectory of different objects in a sequence, usually a video. In recent years, with the rise of Deep Learning, the algorithms that provide a solution to this problem have benefited from the representational power of deep models. This paper provides a comprehensive survey on works that employ Deep Learning models to solve the task of MOT on single-camera videos. Four main steps in MOT algorithms are identified, and an in-depth review of how Deep Learning was employed in each one of these stages is presented. A complete experimental comparison of the presented works on the three MOTChallenge datasets is also provided, identifying a number of similarities among the top-performing methods and presenting some possible future research directions.

Key facts. Cited by 107 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Jul 2019.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 24; 2022: 25; 2023: 23; 2024: 11; 2025: 21; 2026: 3.

107 papers.

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  1. 2022Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusioncited by 162
  2. 2023EgoHumans: An Egocentric 3D Multi-Human Benchmarkcited by 60
  3. 2021DEFT: Detection Embeddings for Trackingcited by 56
  4. 2021RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representationcited by 52
  5. 2021A Survey of Sound Source Localization with Deep Learning Methodscited by 46
  6. 2021Learning a Proposal Classifier for Multiple Object Trackingcited by 42
  7. 2021Tracking Pedestrian Heads in Dense Crowdcited by 42
  8. 2022AnimalTrack: A Benchmark for Multi-Animal Tracking in the Wildcited by 37
  9. 2023Learning Object State Changes in Videos: An Open-World Perspectivecited by 36
  10. 2023A Survey on Deep Learning-Based Monocular Spacecraft Pose Estimation: Current State, Limitations and Prospectscited by 30
  11. 2022Continual Learning with Bayesian Model based on a Fixed Pre-trained Feature Extractorcited by 27
  12. 2021Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmarkcited by 25
38 more
  1. 2021Regular Polytope Networkscited by 24
  2. 2021Near-field Perception for Low-Speed Vehicle Automation using Surround-view Fisheye Camerascited by 24
  3. 2022The Caltech Fish Counting Dataset: A Benchmark for Multiple-Object Tracking and Countingcited by 24
  4. 2023RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloudcited by 21
  5. 2022Global Instance Tracking: Locating Target More Like Humanscited by 18
  6. 2023Real-time Neural Network Inference on Extremely Weak Devices: Agile Offloading with Explainable AIcited by 17
  7. 2022EmbedTrack -- Simultaneous Cell Segmentation and Tracking Through Learning Offsets and Clustering Bandwidthscited by 16
  8. 2021Tracking People by Predicting 3D Appearance, Location & Posecited by 15
  9. 2022Transformers for Multi-Object Tracking on Point Cloudscited by 14
  10. 2023S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representationscited by 12
  11. 2022Visual Adversarial Attacks and Defenses in the Physical World: A Surveycited by 11
  12. 2022SOTVerse: A User-defined Task Space of Single Object Trackingcited by 10
  13. 2023Transformers in Single Object Tracking: An Experimental Surveycited by 10
  14. 2024Computer Vision for Primate Behavior Analysis in the Wildcited by 10
  15. 2022A Region-Based Deep Learning Approach to Automated Retail Checkoutcited by 9
  16. 2023Acquiring Weak Annotations for Tumor Localization in Temporal and Volumetric Datacited by 9
  17. 2021Online Clustering-based Multi-Camera Vehicle Tracking in Scenarios with overlapping FOVscited by 8
  18. 2022Towards PAC Multi-Object Detection and Trackingcited by 8
  19. 2022Recent Advances in Embedding Methods for Multi-Object Tracking: A Surveycited by 8
  20. 2021CFTrack: Center-based Radar and Camera Fusion for 3D Multi-Object Trackingcited by 7
  21. 2022Edge Video Analytics: A Survey on Applications, Systems and Enabling Techniquescited by 7
  22. 2022Multi-view Tracking, Re-ID, and Social Network Analysis of a Flock of Visually Similar Birds in an Outdoor Aviarycited by 7
  23. 2023Objects do not disappear: Video object detection by single-frame object location anticipationcited by 7
  24. 2025O-MaMa: Learning Object Mask Matching between Egocentric and Exocentric Viewscited by 7
  25. 2021Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learningcited by 6
  26. 2022InterTrack: Interaction Transformer for 3D Multi-Object Trackingcited by 6
  27. 2023SpikeMOT: Event-based Multi-Object Tracking with Sparse Motion Featurescited by 6
  28. 2021Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Studycited by 5
  29. 2021Unlocking the potential of deep learning for marine ecology: overview, applications, and outlookcited by 5
  30. 2022Can Deep Learning be Applied to Model-Based Multi-Object Tracking?cited by 5
  31. 2025OSCAR: Object Status and Contextual Awareness for Recipes to Support Non-Visual Cookingcited by 5
  32. 2025WildLive: Near Real-time Visual Wildlife Tracking onboard UAVscited by 5
  33. 2024Engineering an Efficient Object Tracker for Non-Linear Motioncited by 4
  34. 2025Deep Learning-Based Multi-Object Tracking: A Comprehensive Survey from Foundations to State-of-the-Artcited by 4
  35. 2022Optical tracking in team sportscited by 3
  36. 2023TAU: A Framework for Video-Based Traffic Analytics Leveraging Artificial Intelligence and Unmanned Aerial Systemscited by 3
  37. 2023A review of UAV Visual Detection and Tracking Methodscited by 3
  38. 2023The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theorycited by 3

50 most cited of 107 All 107 (JSON)