mlsanityData to 14 Oct 2026

RC-GeoCP: Geometric Consensus for 4D Radar-Camera Collaborative Perception

arXiv 2603.00654 ↗First posted 28 Feb 2026cs.CVcited by 2

Not on the map. Why?

Abstract (arXiv)

Collaborative perception (CP) extends sensing range through feature sharing, but most systems remain LiDAR-centric. Camera and 4D radar sensing combines dense semantics with lower-cost range--velocity measurements, yet exploiting their complementarity across agents remains difficult. Camera depth ambiguity produces spatially diffuse BEV evidence, while sparse transmission couples the choice of evidence to its subsequent contribution. Separate acquisition and aggregation objectives can assign conflicting source preferences to the retained evidence. We propose RC-GeoCP, connecting radar-grounded representation with persistent receiver--source attribution. Geometric Structure Rectification (GSR) uses radar-conditioned deformable sampling and gated calibration to construct grounded BEV features before communication. On these features, Uncertainty-Aware Communication (UAC) combines receiver demand with semantic confidence and radar support in a pre-delivery responsibility field that selects sparse support within fixed quotas. The Consensus-Driven Assembler (CDA) maps the same field into a bounded source mixture, carrying acquisition preferences into assembly. Persistent attribution coordinates spatial selection and source weighting across sparse transmission. Across two datasets and three aggregation backbones, RC-GeoCP consistently improves detection. Its sparse model retains 98.6%/96.6% of dense [email protected] at 10.88/4.95 MB per link. Code will be released.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 42 of its 54 references that are in the map. First posted on arXiv 28 Feb 2026.

Builds on

42 of 54 references.

References · 42

  1. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,218
  2. 2020Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Dcited by 1,044
  3. 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 572
  4. 2022V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformercited by 320
  5. 2021OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communicationcited by 304
  6. 2020V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Predictioncited by 292
  7. 2022DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detectioncited by 273
  8. 2022Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Mapscited by 255
  9. 2022CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformerscited by 227
  10. 2021Learning Distilled Collaboration Graph for Multi-Agent Perceptioncited by 194
  11. 2022Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detectioncited by 178
  12. 2019F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Cloudscited by 171
30 more
  1. 2020CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detectioncited by 161
  2. 2020When2com: Multi-Agent Perception via Communication Graph Groupingcited by 157
  3. 2023V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perceptioncited by 155
  4. 2022Robust Collaborative 3D Object Detection in Presence of Pose Errorscited by 129
  5. 2020Who2com: Collaborative Perception via Learnable Handshake Communicationcited by 127
  6. 2023PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentationcited by 115
  7. 2024RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detectioncited by 82
  8. 2023HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with vision transformercited by 70
  9. 2024Communication-Efficient Collaborative Perception via Information Filling with Codebookcited by 68
  10. 2022CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformercited by 67
  11. 2023LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusioncited by 58
  12. 2024V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Predictioncited by 31
  13. 2025CoSDH: Communication-Efficient Collaborative Perception via Supply-Demand Awareness and Intermediate-Late Hybridizationcited by 28
  14. 2024OmniHD-Scenes: A Next-Generation Multimodal Dataset for Autonomous Drivingcited by 27
  15. 2023Survey on LiDAR Perception in Adverse Weather Conditionscited by 24
  16. 2024V2X-Radar: A Multi-modal Dataset with 4D Radar for Cooperative Perceptioncited by 22
  17. 2025Doracamom: Joint 3D Detection and Occupancy Prediction with Multi-view 4D Radars and Cameras for Omnidirectional Perceptioncited by 22
  18. 2024RaCFormer: Towards High-Quality 3D Object Detection via Query-based Radar-Camera Fusioncited by 19
  19. 2024V2X-R: Cooperative LiDAR-4D Radar Fusion with Denoising Diffusion for 3D Object Detectioncited by 18
  20. 2025TraF-Align: Trajectory-aware Feature Alignment for Asynchronous Multi-agent Perceptioncited by 15
  21. 2025RaGS: Unleashing 3D Gaussian Splatting from 4D Radar and Monocular Cues for 3D Object Detectioncited by 9
  22. 2025CoST: Efficient Collaborative Perception From Unified Spatiotemporal Perspectivecited by 8
  23. 2024RCDN: Towards Robust Camera-Insensitivity Collaborative Perception via Dynamic Feature-based 3D Neural Modelingcited by 6
  24. 2025SlimComm: Doppler-Guided Sparse Queries for Bandwidth-Efficient Cooperative 3-D Perceptioncited by 5
  25. 2025SparseCoop: Cooperative Perception with Kinematic-Grounded Queriescited by 4
  26. 2026SD4R: Sparse-to-Dense Learning for 3D Object Detection with 4D Radarcited by 4
  27. 2025FocalComm: Hard Instance-Aware Multi-Agent Perceptioncited by 2
  28. 2026COOPERTRIM: Adaptive Data Selection for Uncertainty-Aware Cooperative Perceptioncited by 2
  29. 2025MLF-4DRCNet: Multi-Level Fusion with 4D Radar and Camera for 3D Object Detection in Autonomous Drivingcited by 1
  30. 2025M^3Detection: Multi-Frame Multi-Level Feature Fusion for Multi-Modal 3D Object Detection with Camera and 4D Imaging Radarcited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 20264DR360: State Reasoning for Joint 3D Detection and Occupancy Prediction in 4D Radar-Camera Full-Scene Perceptioncited by 2
  2. 2026SGDet3D++: Geometry-Grounded Semantics for 4D Radar and Camera 3D Object Detectioncited by 0