mlsanityData to 7 Oct 2026

Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles

arXiv 2204.09151 ↗First posted 19 Apr 2022cs.CVcited by 19

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Abstract (arXiv)

The development of autonomous vehicles provides an opportunity to have a complete set of camera sensors capturing the environment around the car. Thus, it is important for object detection and tracking to address new challenges, such as achieving consistent results across views of cameras. To address these challenges, this work presents a new Global Association Graph Model with Link Prediction approach to predict existing tracklets location and link detections with tracklets via cross-attention motion modeling and appearance re-identification. This approach aims at solving issues caused by inconsistent 3D object detection. Moreover, our model exploits to improve the detection accuracy of a standard 3D object detector in the nuScenes detection challenge. The experimental results on the nuScenes dataset demonstrate the benefits of the proposed method to produce SOTA performance on the existing vision-based tracking dataset.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 36 of its 48 references that are in the map. First posted on arXiv 19 Apr 2022.

Builds on

36 of 48 references.

References · 36

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  7. 2020Training data-efficient image transformers & distillation through attentioncited by 4,560
  8. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  9. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  10. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,410
  11. 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,361
  12. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
24 more
  1. 2019Objects as Pointscited by 1,172
  2. 2020Center-based 3D Object Detection and Trackingcited by 1,143
  3. 2018PointRCNN: 3D Object Proposal Generation and Detection from Point Cloudcited by 939
  4. 2019Argoverse: 3D Tracking and Forecasting with Rich Mapscited by 728
  5. 2019Stand-Alone Self-Attention in Vision Modelscited by 542
  6. 2021TrackFormer: Multi-Object Tracking with Transformerscited by 515
  7. 2020Tracking Objects as Pointscited by 483
  8. 2020End-to-End Video Instance Segmentation with Transformerscited by 443
  9. 2020TransTrack: Multiple Object Tracking with Transformercited by 370
  10. 2019Class-balanced Grouping and Sampling for Point Cloud 3D Object Detectioncited by 350
  11. 2019Omni-Scale Feature Learning for Person Re-Identificationcited by 292
  12. 2019Disentangling Monocular 3D Object Detectioncited by 215
  13. 2018Scaling Neural Machine Translationcited by 204
  14. 2020GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learningcited by 113
  15. 2021Monocular Quasi-Dense 3D Object Trackingcited by 80
  16. 2018Joint Monocular 3D Vehicle Detection and Trackingcited by 77
  17. 2019Online Multi-Object Tracking with Dual Matching Attention Networkscited by 77
  18. 2020Probabilistic 3D Multi-Object Tracking for Autonomous Drivingcited by 64
  19. 2020AB3DMOT: A Baseline for 3D Multi-Object Tracking and New Evaluation Metricscited by 63
  20. 2021DEFT: Detection Embeddings for Trackingcited by 56
  21. 2017Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanismcited by 48
  22. 2021DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Trackingcited by 31
  23. 2017Accurate Single Stage Detector Using Recurrent Rolling Convolutioncited by 27
  24. 2017Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Projectcited by 19

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 6; 2024: 7; 2025: 3; 2026: 1.

19 papers.

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  1. 2023Type-to-Track: Retrieve Any Object via Prompt-based Trackingcited by 24
  2. 2023HIG: Hierarchical Interlacement Graph Approach to Scene Graph Generation in Video Understandingcited by 21
  3. 2024QClusformer: A Quantum Transformer-based Framework for Unsupervised Visual Clusteringcited by 11
  4. 2023VT-Former: An Exploratory Study on Vehicle Trajectory Prediction for Highway Surveillance through Graph Isomorphism and Transformercited by 10
  5. 2022Depth Perspective-aware Multiple Object Trackingcited by 8
  6. 2022Multi-Camera Multi-Object Tracking on the Move via Single-Stage Global Association Approachcited by 7
  7. 2023Z-GMOT: Zero-shot Generic Multiple Object Trackingcited by 7
  8. 2024BRACTIVE: A Brain Activation Approach to Human Visual Brain Learningcited by 6
  9. 2024COBRA: A Continual Learning Approach to Vision-Brain Understandingcited by 4
  10. 2023Brainformer: Mimic Human Visual Brain Functions to Machine Vision Models via fMRIcited by 3
  11. 2023UTOPIA: Unconstrained Tracking Objects without Preliminary Examination via Cross-Domain Adaptationcited by 1
  12. 2024CarcassFormer: An End-to-end Transformer-based Framework for Simultaneous Localization, Segmentation and Classification of Poultry Carcass Defectcited by 1
7 more
  1. 2024Inverse Neural Rendering for Explainable Multi-Object Trackingcited by 1
  2. 2024DINTR: Tracking via Diffusion-based Interpolationcited by 1
  3. 2024TrackMe:A Simple and Effective Multiple Object Tracking Annotation Toolcited by 0
  4. 2025MGSfM: Multi-Camera Geometry Driven Global Structure-from-Motioncited by 0
  5. 2025BRAIN: Bias-Mitigation Continual Learning Approach to Vision-Brain Understandingcited by 0
  6. 2025Stable Multi-Drone GNSS Tracking System for Marine Robotscited by 0
  7. 2026TriBand-BEV: Real-Time LiDAR-Only 3D Pedestrian Detection via Height-Aware BEV and High-Resolution Feature Fusioncited by 0