mlsanityData to 14 Oct 2026

Immortal Tracker: Tracklet Never Dies

arXiv 2111.13672 ↗First posted 26 Nov 2021cs.CVcited by 42

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Abstract (arXiv)

Previous online 3D Multi-Object Tracking(3DMOT) methods terminate a tracklet when it is not associated with new detections for a few frames. But if an object just goes dark, like being temporarily occluded by other objects or simply getting out of FOV, terminating a tracklet prematurely will result in an identity switch. We reveal that premature tracklet termination is the main cause of identity switches in modern 3DMOT systems. To address this, we propose Immortal Tracker, a simple tracking system that utilizes trajectory prediction to maintain tracklets for objects gone dark. We employ a simple Kalman filter for trajectory prediction and preserve the tracklet by prediction when the target is not visible. With this method, we can avoid 96% vehicle identity switches resulting from premature tracklet termination. Without any learned parameters, our method achieves a mismatch ratio at the 0.0001 level and competitive MOTA for the vehicle class on the Waymo Open Dataset test set. Our mismatch ratio is tens of times lower than any previously published method. Similar results are reported on nuScenes. We believe the proposed Immortal Tracker can offer a simple yet powerful solution for pushing the limit of 3DMOT. Our code is available at https://github.com/ImmortalTracker/ImmortalTracker.

Key facts. Cited by 42 papers in the map (data through 14 Oct 2026). Builds on 21 of its 30 references that are in the map. First posted on arXiv 26 Nov 2021.

Builds on

21 of 30 references.

References · 21

  1. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,523
  2. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,451
  3. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,715
  4. 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,368
  5. 2020Center-based 3D Object Detection and Trackingcited by 1,144
  6. 2018PointRCNN: 3D Object Proposal Generation and Detection from Point Cloudcited by 941
  7. 2017Simple Online and Realtime Tracking with a Deep Association Metriccited by 910
  8. 2016Simple Online and Realtime Trackingcited by 868
  9. 2020Tracking Objects as Pointscited by 483
  10. 2021RangeDet:In Defense of Range View for LiDAR-based 3D Object Detectioncited by 140
  11. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  12. 2020GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learningcited by 113
9 more
  1. 2021SimpleTrack: Understanding and Rethinking 3D Multi-object Trackingcited by 103
  2. 2019The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenescited by 80
  3. 2020Probabilistic 3D Multi-Modal, Multi-Object Tracking for Autonomous Drivingcited by 73
  4. 2020Probabilistic 3D Multi-Object Tracking for Autonomous Drivingcited by 64
  5. 20193D Multi-Object Tracking: A Baseline and New Evaluation Metricscited by 47
  6. 2021Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Trackingcited by 47
  7. 2020Improving 3D Object Detection through Progressive Population Based Augmentationcited by 41
  8. 2021Learnable Online Graph Representations for 3D Multi-Object Trackingcited by 38
  9. 2021Score refinement for confidence-based 3D multi-object trackingcited by 32

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 5; 2023: 16; 2024: 11; 2025: 6; 2026: 4.

42 papers.

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  1. 2022Planning-oriented Autonomous Drivingcited by 1,087
  2. 2024Enhancing End-to-End Autonomous Driving with Latent World Modelcited by 166
  3. 2023NeuRAD: Neural Rendering for Autonomous Drivingcited by 150
  4. 2023Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Trackingcited by 54
  5. 2024ADA-Track++: End-to-End Multi-Camera 3D Multi-Object Tracking with Alternating Detection and Associationcited by 33
  6. 2023DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Cloudscited by 31
  7. 2023Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detectioncited by 28
  8. 20233DMOTFormer: Graph Transformer for Online 3D Multi-Object Trackingcited by 21
  9. 2023ByteTrackV2: 2D and 3D Multi-Object Tracking by Associating Every Detection Boxcited by 20
  10. 2023MotionTrack: End-to-End Transformer-based Multi-Object Tracing with LiDAR-Camera Fusioncited by 19
  11. 20224D Unsupervised Object Discoverycited by 18
  12. 2024DualAD: Disentangling the Dynamic and Static World for End-to-End Drivingcited by 17
30 more
  1. 2024MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Drivingcited by 17
  2. 2022GNN-PMB: A Simple but Effective Online 3D Multi-Object Tracker without Bells and Whistlescited by 15
  3. 2023TrajectoryFormer: 3D Object Tracking Transformer with Predictive Trajectory Hypothesescited by 14
  4. 2022Neural Enhanced Belief Propagation for Multiobject Trackingcited by 11
  5. 2022Minkowski Tracker: A Sparse Spatio-Temporal R-CNN for Joint Object Detection and Trackingcited by 9
  6. 2023LEGO: Learning and Graph-Optimized Modular Tracker for Online Multi-Object Tracking with Point Cloudscited by 9
  7. 2024RobMOT: Robust 3D Multi-Object Tracking by Observational Noise and State Estimation Drift Mitigation on LiDAR PointCloudcited by 9
  8. 20233D Video Object Detection with Learnable Object-Centric Global Optimizationcited by 7
  9. 2023Offline Tracking with Object Permanencecited by 7
  10. 2024ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Drivingcited by 6
  11. 2026TruckDrive: Long-Range Autonomous Highway Driving Datasetcited by 5
  12. 2023Streaming Motion Forecasting for Autonomous Drivingcited by 4
  13. 20243D Single-object Tracking in Point Clouds with High Temporal Variationcited by 4
  14. 20233D Multi-Object Tracking Based on Uncertainty-Guided Data Associationcited by 3
  15. 2023Frame Fusion with Vehicle Motion Prediction for 3D Object Detectioncited by 3
  16. 2024Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object Detectioncited by 3
  17. 2025Bayesian Multiobject Tracking With Neural-Enhanced Motion and Measurement Modelscited by 3
  18. 2023Tracking Objects with 3D Representation from Videoscited by 2
  19. 2023Weakly Supervised 3D Object Detection with Multi-Stage Generalizationcited by 2
  20. 2024Open3DTrack: Towards Open-Vocabulary 3D Multi-Object Trackingcited by 2
  21. 2025OV-SCAN: Semantically Consistent Alignment for Novel Object Discovery in Open-Vocabulary 3D Object Detectioncited by 2
  22. 2025LiDAR MOT-DETR: A LiDAR-based Two-Stage Transformer for 3D Multiple Object Trackingcited by 2
  23. 2026Offline-Poly: A Polyhedral Framework For Offline 3D Multi-Object Trackingcited by 2
  24. 2024STT: Stateful Tracking with Transformers for Autonomous Drivingcited by 1
  25. 2025Towards Accurate State Estimation: Motion Dynamics Kalman Filter for 3D Multi-Object Trackingcited by 1
  26. 2025M^3Detection: Multi-Frame Multi-Level Feature Fusion for Multi-Modal 3D Object Detection with Camera and 4D Imaging Radarcited by 1
  27. 2026UniLiPs: Unified LiDAR Pseudo-Labeling with Geometry-Grounded Dynamic Scene Decompositioncited by 1
  28. 20243D Object Visibility Prediction in Autonomous Drivingcited by 0
  29. 2025Delving into Dynamic Scene Cue-Consistency for Robust 3D Multi-Object Trackingcited by 0
  30. 2026AutoMine Solution for AV2 2026 Scenario Mining Challengecited by 0