mlsanityData to 14 Oct 2026

Collective Perception Datasets for Autonomous Driving: A Comprehensive Review

arXiv 2405.16973 ↗First posted 27 May 2024cs.CVcited by 4

Not on the map. Why?

Abstract (arXiv)

To ensure safe operation of autonomous vehicles in complex urban environments, complete perception of the environment is necessary. However, due to environmental conditions, sensor limitations, and occlusions, this is not always possible from a single point of view. To address this issue, collective perception is an effective method. Realistic and large-scale datasets are essential for training and evaluating collective perception methods. This paper provides the first comprehensive technical review of collective perception datasets in the context of autonomous driving. The survey analyzes existing V2V and V2X datasets, categorizing them based on different criteria such as sensor modalities, environmental conditions, and scenario variety. The focus is on their applicability for the development of connected automated vehicles. This study aims to identify the key criteria of all datasets and to present their strengths, weaknesses, and anomalies. Finally, this survey concludes by making recommendations regarding which dataset is most suitable for collective 3D object detection, tracking, and semantic segmentation.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 27 of its 37 references that are in the map. First posted on arXiv 27 May 2024.

Builds on

27 of 37 references.

References · 27

  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. 2017CARLA: An Open Urban Driving Simulatorcited by 2,449
  4. 2019PIXOR: Real-time 3D Object Detection from Point Cloudscited by 358
  5. 2022V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformercited by 320
  6. 2021OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communicationcited by 304
  7. 2020V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Predictioncited by 292
  8. 2022DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detectioncited by 273
  9. 2021Learning Distilled Collaboration Graph for Multi-Agent Perceptioncited by 194
  10. 2019F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Cloudscited by 171
  11. 2019Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Cloudscited by 165
  12. 2022V2X-Sim: Multi-Agent Collaborative Perception Dataset and Benchmark for Autonomous Drivingcited by 157
15 more
  1. 2023V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perceptioncited by 155
  2. 2020LiDARsim: Realistic LiDAR Simulation by Leveraging the Real Worldcited by 137
  3. 2019CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identificationcited by 119
  4. 2023V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecastingcited by 114
  5. 2019Cooperative Perception for 3D Object Detection in Driving Scenarios using Infrastructure Sensorscited by 110
  6. 2023DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Drivingcited by 73
  7. 2024TUMTraf V2X Cooperative Perception Datasetcited by 67
  8. 2024V2X-Real: a Large-Scale Dataset for Vehicle-to-Everything Cooperative Perceptioncited by 66
  9. 2023Asynchrony-Robust Collaborative Perception via Bird's Eye View Flowcited by 58
  10. 2022A9-Dataset: Multi-Sensor Infrastructure-Based Dataset for Mobility Researchcited by 40
  11. 2021IPS300+: a Challenging Multimodal Dataset for Intersection Perception Systemcited by 26
  12. 2021Fast and Robust Registration of Partially Overlapping Point Cloudscited by 22
  13. 2022DOLPHINS: Dataset for Collaborative Perception enabled Harmonious and Interconnected Self-drivingcited by 21
  14. 2021Weakly Supervised Training of Monocular 3D Object Detectors Using Wide Baseline Multi-view Traffic Camera Datacited by 11
  15. 2023A9 Intersection Dataset: All You Need for Urban 3D Camera-LiDAR Roadside Perceptioncited by 4

Built on by

Cited by year

Citing papers per year: 2024: 1; 2025: 3.

4 papers.

  1. 2024SCOPE: A Synthetic Multi-Modal Dataset for Collective Perception Including Physical-Correct Weather Conditionscited by 8
  2. 2025Collaborative Perception Datasets for Autonomous Driving: A Reviewcited by 8
  3. 2025A Synthetic Benchmark for Collaborative 3D Semantic Occupancy Prediction in V2X-Enabled Autonomous Drivingcited by 1
  4. 2025DenoiseCP-Net: Efficient Collective Perception in Adverse Weather via Joint LiDAR-Based 3D Object Detection and Denoisingcited by 0