mlsanityData to 7 Oct 2026

Learnable Online Graph Representations for 3D Multi-Object Tracking

arXiv 2104.11747 ↗First posted 23 Apr 2021cs.CV cs.ROcited by 38

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Abstract (arXiv)

Tracking of objects in 3D is a fundamental task in computer vision that finds use in a wide range of applications such as autonomous driving, robotics or augmented reality. Most recent approaches for 3D multi object tracking (MOT) from LIDAR use object dynamics together with a set of handcrafted features to match detections of objects. However, manually designing such features and heuristics is cumbersome and often leads to suboptimal performance. In this work, we instead strive towards a unified and learning based approach to the 3D MOT problem. We design a graph structure to jointly process detection and track states in an online manner. To this end, we employ a Neural Message Passing network for data association that is fully trainable. Our approach provides a natural way for track initialization and handling of false positive detections, while significantly improving track stability. We show the merit of the proposed approach on the publicly available nuScenes dataset by achieving state-of-the-art performance of 65.6% AMOTA and 58% fewer ID-switches.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). Builds on 21 of its 35 references that are in the map. First posted on arXiv 23 Apr 2021.

Builds on

21 of 35 references.

References · 21

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  3. 2017Mask R-CNNcited by 7,259
  4. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  5. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,436
  6. 2020Center-based 3D Object Detection and Trackingcited by 1,143
  7. 2019EfficientDet: Scalable and Efficient Object Detectioncited by 1,018
  8. 2019Argoverse: 3D Tracking and Forecasting with Rich Mapscited by 728
  9. 2016MOT16: A Benchmark for Multi-Object Trackingcited by 531
  10. 2019Tracking without bells and whistlescited by 382
  11. 2020MOT20: A benchmark for multi object tracking in crowded scenescited by 355
  12. 2019Class-balanced Grouping and Sampling for Point Cloud 3D Object Detectioncited by 350
9 more
  1. 2019Learning a Neural Solver for Multiple Object Trackingcited by 198
  2. 2015MOTChallenge 2015: Towards a Benchmark for Multi-Target Trackingcited by 133
  3. 2019Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactionscited by 117
  4. 2020GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learningcited by 113
  5. 2017Learning non-maximum suppressioncited by 112
  6. 2020Probabilistic 3D Multi-Object Tracking for Autonomous Drivingcited by 64
  7. 2019Robust Multi-Modality Multi-Object Trackingcited by 56
  8. 2020Simple Unsupervised Multi-Object Trackingcited by 33
  9. 2020Action Sequence Predictions of Vehicles in Urban Environments using Map and Social Contextcited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 14; 2023: 11; 2024: 3; 2025: 5; 2026: 2.

38 papers.

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  1. 2023VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Trackingcited by 221
  2. 2021Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Trackingcited by 165
  3. 2021SimpleTrack: Understanding and Rethinking 3D Multi-object Trackingcited by 102
  4. 2022MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queriescited by 90
  5. 2023FocalFormer3D : Focusing on Hard Instance for 3D Object Detectioncited by 58
  6. 2023Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Trackingcited by 54
  7. 2022CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusioncited by 50
  8. 2021Immortal Tracker: Tracklet Never Diescited by 42
  9. 2022PolarMOT: How Far Can Geometric Relations Take Us in 3D Multi-Object Tracking?cited by 29
  10. 2022Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?cited by 28
  11. 20223D Multi-Object Tracking Using Graph Neural Networks with Cross-Edge Modality Attentioncited by 27
  12. 2022TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTMcited by 26
26 more
  1. 2022Adiabatic Quantum Computing for Multi Object Trackingcited by 22
  2. 2022ShaSTA: Modeling Shape and Spatio-Temporal Affinities for 3D Multi-Object Trackingcited by 21
  3. 20233DMOTFormer: Graph Transformer for Online 3D Multi-Object Trackingcited by 21
  4. 2023RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloudcited by 21
  5. 2023ByteTrackV2: 2D and 3D Multi-Object Tracking by Associating Every Detection Boxcited by 20
  6. 2022GNN-PMB: A Simple but Effective Online 3D Multi-Object Tracker without Bells and Whistlescited by 15
  7. 20234D-Former: Multimodal 4D Panoptic Segmentationcited by 12
  8. 2022Neural Enhanced Belief Propagation for Multiobject Trackingcited by 11
  9. 2024Fast-Poly: A Fast Polyhedral Framework For 3D Multi-Object Trackingcited by 11
  10. 2022Neural Enhanced Belief Propagation for Data Association in Multiobject Trackingcited by 10
  11. 2022SpOT: Spatiotemporal Modeling for 3D Object Trackingcited by 10
  12. 2022Minkowski Tracker: A Sparse Spatio-Temporal R-CNN for Joint Object Detection and Trackingcited by 9
  13. 2023LEGO: Learning and Graph-Optimized Modular Tracker for Online Multi-Object Tracking with Point Cloudscited by 9
  14. 20233D Multiple Object Tracking on Autonomous Driving: A Literature Reviewcited by 4
  15. 2024A New Architecture for Neural Enhanced Multiobject Trackingcited by 3
  16. 2025IMM-MOT: A Novel 3D Multi-object Tracking Framework with Interacting Multiple Model Filtercited by 2
  17. 2023BOTT: Box Only Transformer Tracker for 3D Object Trackingcited by 1
  18. 2023ShaSTA-Fuse: Camera-LiDAR Sensor Fusion to Model Shape and Spatio-Temporal Affinities for 3D Multi-Object Trackingcited by 1
  19. 2025Easy-Poly: An Easy Polyhedral Framework For 3D Multi-Object Trackingcited by 1
  20. 2025OptiPMB: Enhancing 3D Multi-Object Tracking with Optimized Poisson Multi-Bernoulli Filteringcited by 1
  21. 2022Interpretable Deep Trackingcited by 0
  22. 2024RegTrack: Simplicity Beneath Complexity in Robust Multi-Modal 3D Multi-Object Trackingcited by 0
  23. 2025S3MOT: Monocular 3D Object Tracking with Selective State Space Modelcited by 0
  24. 2025End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaborationcited by 0
  25. 2026Seg2Track++: Probabilistic Track Validation and Data Association for Multi-Object Tracking and Segmentationcited by 0
  26. 2026A Review Of Robotic World Models For Dynamic Environments Based On Factor And Scene Graphscited by 0