Data to 7 Oct 2026

V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction

arXiv 2008.07519 ↗First posted 17 Aug 2020cs.CVcited by 292

Not on the map. Why?

Cited by 27 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this paper, we explore the use of vehicle-to-vehicle (V2V) communication to improve the perception and motion forecasting performance of self-driving vehicles. By intelligently aggregating the information received from multiple nearby vehicles, we can observe the same scene from different viewpoints. This allows us to see through occlusions and detect actors at long range, where the observations are very sparse or non-existent. We also show that our approach of sending compressed deep feature map activations achieves high accuracy while satisfying communication bandwidth requirements.

Key facts. Cited by 292 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Aug 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 10; 2022: 25; 2023: 52; 2024: 61; 2025: 82; 2026: 62.

292 papers.

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2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
2022V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformercited by 320
2023VoxFormer: Sparse Voxel Transformer for Camera-based 3D Semantic Scene Completioncited by 306
2021OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communicationcited by 304
2022DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detectioncited by 270
2022Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Mapscited by 255
2022CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformerscited by 227
2021Learning Distilled Collaboration Graph for Multi-Agent Perceptioncited by 194
2022V2X-Sim: Multi-Agent Collaborative Perception Dataset and Benchmark for Autonomous Drivingcited by 157
2023V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perceptioncited by 155
20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
2022Robust Collaborative 3D Object Detection in Presence of Pose Errorscited by 129

38 more

2023V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecastingcited by 114
2021LaneRCNN: Distributed Representations for Graph-Centric Motion Forecastingcited by 112
2022COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehiclescited by 95
2023Collaborative Perception in Autonomous Driving: Methods, Datasets and Challengescited by 87
2024An Extensible Framework for Open Heterogeneous Collaborative Perceptioncited by 87
2022Latency-Aware Collaborative Perceptioncited by 86
2021VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehiclescited by 81
2023Collaboration Helps Camera Overtake LiDAR in 3D Detectioncited by 81
2022Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Taskcited by 79
2023HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with vision transformercited by 70
2024Communication-Efficient Collaborative Perception via Information Filling with Codebookcited by 67
2024A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlookcited by 65
2022Bridging the Domain Gap for Multi-Agent Perceptioncited by 60
2023Asynchrony-Robust Collaborative Perception via Bird's Eye View Flowcited by 58
2023Spatio-Temporal Domain Awareness for Multi-Agent Collaborative Perceptioncited by 52
2021Adversarial Attacks On Multi-Agent Communicationcited by 48
2022Learning for Vehicle-to-Vehicle Cooperative Perception under Lossy Communicationcited by 47
2024V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Modelscited by 47
2022Uncertainty Quantification of Collaborative Detection for Self-Drivingcited by 46
2021Keypoints-Based Deep Feature Fusion for Cooperative Vehicle Detection of Autonomous Drivingcited by 45
2025STAMP: Scalable Task And Model-agnostic Collaborative Perceptioncited by 44
2024End-to-End Autonomous Driving through V2X Cooperationcited by 42
2023CORE: Cooperative Reconstruction for Multi-Agent Perceptioncited by 41
2024AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learningcited by 40
2023Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perceptioncited by 38
2023Among Us: Adversarially Robust Collaborative Perception by Consensuscited by 37
2024RCooper: A Real-world Large-scale Dataset for Roadside Cooperative Perceptioncited by 37
2023DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object Detectioncited by 34
2024Collaborative Semantic Occupancy Prediction with Hybrid Feature Fusion in Connected Automated Vehiclescited by 33
2024Collaborative Perception for Connected and Autonomous Driving: Challenges, Possible Solutions and Opportunitiescited by 32
2023Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detectioncited by 31
2024V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Predictioncited by 31
2022Behavioral Intention Prediction in Driving Scenes: A Surveycited by 30
2022Adaptive Feature Fusion for Cooperative Perception using LiDAR Point Cloudscited by 29
2023UMC: A Unified Bandwidth-efficient and Multi-resolution based Collaborative Perception Frameworkcited by 29
2022V2XP-ASG: Generating Adversarial Scenes for Vehicle-to-Everything Perceptioncited by 28
2025V2V-LLM: Vehicle-to-Vehicle Cooperative Autonomous Driving with Multimodal Large Language Modelscited by 27
2025CoSDH: Communication-Efficient Collaborative Perception via Supply-Demand Awareness and Intermediate-Late Hybridizationcited by 27

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