mlsanityData to 7 Oct 2026

Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds

arXiv 1905.05265 ↗First posted 13 May 2019cs.CVcited by 165

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Abstract (arXiv)

Autonomous vehicles may make wrong decisions due to inaccurate detection and recognition. Therefore, an intelligent vehicle can combine its own data with that of other vehicles to enhance perceptive ability, and thus improve detection accuracy and driving safety. However, multi-vehicle cooperative perception requires the integration of real world scenes and the traffic of raw sensor data exchange far exceeds the bandwidth of existing vehicular networks. To the best our knowledge, we are the first to conduct a study on raw-data level cooperative perception for enhancing the detection ability of self-driving systems. In this work, relying on LiDAR 3D point clouds, we fuse the sensor data collected from different positions and angles of connected vehicles. A point cloud based 3D object detection method is proposed to work on a diversity of aligned point clouds. Experimental results on KITTI and our collected dataset show that the proposed system outperforms perception by extending sensing area, improving detection accuracy and promoting augmented results. Most importantly, we demonstrate it is possible to transmit point clouds data for cooperative perception via existing vehicular network technologies.

Key facts. Cited by 165 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 May 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 18; 2023: 35; 2024: 29; 2025: 47; 2026: 32.

165 papers.

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  1. 2022V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformercited by 320
  2. 2021OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communicationcited by 304
  3. 2022CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformerscited by 227
  4. 2021Learning Distilled Collaboration Graph for Multi-Agent Perceptioncited by 194
  5. 2022V2X-Sim: Multi-Agent Collaborative Perception Dataset and Benchmark for Autonomous Drivingcited by 157
  6. 2023V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perceptioncited by 155
  7. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  8. 2023V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecastingcited by 114
  9. 2022COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehiclescited by 95
  10. 2023Collaborative Perception in Autonomous Driving: Methods, Datasets and Challengescited by 87
  11. 2022Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Taskcited by 79
  12. 2024A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlookcited by 65
38 more
  1. 2023Spatio-Temporal Domain Awareness for Multi-Agent Collaborative Perceptioncited by 52
  2. 2022Learning for Vehicle-to-Vehicle Cooperative Perception under Lossy Communicationcited by 47
  3. 2022Uncertainty Quantification of Collaborative Detection for Self-Drivingcited by 46
  4. 2021Keypoints-Based Deep Feature Fusion for Cooperative Vehicle Detection of Autonomous Drivingcited by 45
  5. 2025STAMP: Scalable Task And Model-agnostic Collaborative Perceptioncited by 44
  6. 2024End-to-End Autonomous Driving through V2X Cooperationcited by 42
  7. 2023CORE: Cooperative Reconstruction for Multi-Agent Perceptioncited by 41
  8. 2023Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perceptioncited by 38
  9. 2023Among Us: Adversarially Robust Collaborative Perception by Consensuscited by 37
  10. 2024RCooper: A Real-world Large-scale Dataset for Roadside Cooperative Perceptioncited by 37
  11. 2023DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object Detectioncited by 34
  12. 2022Adaptive Feature Fusion for Cooperative Perception using LiDAR Point Cloudscited by 29
  13. 2023UMC: A Unified Bandwidth-efficient and Multi-resolution based Collaborative Perception Frameworkcited by 29
  14. 2022V2XP-ASG: Generating Adversarial Scenes for Vehicle-to-Everything Perceptioncited by 28
  15. 2023Collaborative Multi-Object Tracking with Conformal Uncertainty Propagationcited by 27
  16. 2025CoSDH: Communication-Efficient Collaborative Perception via Supply-Demand Awareness and Intermediate-Late Hybridizationcited by 27
  17. 2023Interruption-Aware Cooperative Perception for V2X Communication-Aided Autonomous Drivingcited by 25
  18. 2025LangCoop: Collaborative Driving with Languagecited by 25
  19. 2021Distributed Dynamic Map Fusion via Federated Learning for Intelligent Networked Vehiclescited by 24
  20. 2023QUEST: Query Stream for Practical Cooperative Perceptioncited by 23
  21. 2022DOLPHINS: Dataset for Collaborative Perception enabled Harmonious and Interconnected Self-drivingcited by 21
  22. 2022A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperationcited by 21
  23. 2023BM2CP: Efficient Collaborative Perception with LiDAR-Camera Modalitiescited by 20
  24. 2024V2X-R: Cooperative LiDAR-4D Radar Fusion with Denoising Diffusion for 3D Object Detectioncited by 18
  25. 2023DUSA: Decoupled Unsupervised Sim2Real Adaptation for Vehicle-to-Everything Collaborative Perceptioncited by 17
  26. 2023Vehicle-to-Everything Cooperative Perception for Autonomous Drivingcited by 15
  27. 2025Griffin: Aerial-Ground Cooperative Detection and Tracking Dataset and Benchmarkcited by 15
  28. 2025SparseAlign: A Fully Sparse Framework for Cooperative Object Detectioncited by 15
  29. 2025TraF-Align: Trajectory-aware Feature Alignment for Asynchronous Multi-agent Perceptioncited by 15
  30. 2023MACP: Efficient Model Adaptation for Cooperative Perceptioncited by 14
  31. 2024A Survey on Intermediate Fusion Methods for Collaborative Perception Categorized by Real World Challengescited by 13
  32. 2024DSRC: Learning Density-insensitive and Semantic-aware Collaborative Representation against Corruptionscited by 13
  33. 2025CoCMT: Communication-Efficient Cross-Modal Transformer for Collaborative Perceptioncited by 13
  34. 2023Select2Col: Leveraging Spatial-Temporal Importance of Semantic Information for Efficient Collaborative Perceptioncited by 12
  35. 2024V2X-DGW: Domain Generalization for Multi-agent Perception under Adverse Weather Conditionscited by 12
  36. 2024A Survey on Integrated Sensing, Communication, and Computationcited by 12
  37. 2023On Data Fabrication in Collaborative Vehicular Perception: Attacks and Countermeasurescited by 11
  38. 2024What Makes Good Collaborative Views? Contrastive Mutual Information Maximization for Multi-Agent Perceptioncited by 11

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