mlsanityData to 14 Oct 2026

The Components of Collaborative Joint Perception and Prediction -- A Conceptual Framework

arXiv 2501.15860 ↗First posted 27 Jan 2025cs.CVcited by 2

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Abstract (arXiv)

Connected Autonomous Vehicles (CAVs) benefit from Vehicle-to-Everything (V2X) communication, which enables the exchange of sensor data to achieve Collaborative Perception (CP). To reduce cumulative errors in perception modules and mitigate the visual occlusion, this paper introduces a new task, Collaborative Joint Perception and Prediction (Co-P&P), and provides a conceptual framework for its implementation to improve motion prediction of surrounding objects, thereby enhancing vehicle awareness in complex traffic scenarios. The framework consists of two decoupled core modules, Collaborative Scene Completion (CSC) and Joint Perception and Prediction (P&P) module, which simplify practical deployment and enhance scalability. Additionally, we outline the challenges in Co-P&P and discuss future directions for this research area.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 18 of its 31 references that are in the map. First posted on arXiv 27 Jan 2025.

Builds on

18 of 31 references.

References · 18

  1. 2017Attention Is All You Needcited by 60,361
  2. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
  3. 2021Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Datasetcited by 537
  4. 2020V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Predictioncited by 292
  5. 2019F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Cloudscited by 171
  6. 2020PnPNet: End-to-End Perception and Prediction with Tracking in the Loopcited by 144
  7. 2022ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queriescited by 117
  8. 2023V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecastingcited by 114
  9. 2023Collaboration Helps Camera Overtake LiDAR in 3D Detectioncited by 81
  10. 2023DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Drivingcited by 73
  11. 2021A Survey on Deep Domain Adaptation for LiDAR Perceptioncited by 47
  12. 2023CORE: Cooperative Reconstruction for Multi-Agent Perceptioncited by 41
6 more
  1. 2023DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object Detectioncited by 34
  2. 2023UMC: A Unified Bandwidth-efficient and Multi-resolution based Collaborative Perception Frameworkcited by 29
  3. 2022Forecasting from LiDAR via Future Object Detectioncited by 28
  4. 2023Machine Learning for Autonomous Vehicle's Trajectory Prediction: A comprehensive survey, Challenges, and Future Research Directionscited by 23
  5. 2023Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?cited by 22
  6. 2023HPL-ViT: A Unified Perception Framework for Heterogeneous Parallel LiDARs in V2Vcited by 6

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025VALISENS: A Validated Innovative Multi-Sensor System for Cooperative Automated Drivingcited by 1
  2. 2026Towards Collaborative Joint Perception and Prediction: Framework, Baseline Evaluation, and Deployment Perspectivescited by 0