CoST: Efficient Collaborative Perception From Unified Spatiotemporal Perspective
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Abstract (arXiv)
Collaborative perception shares information among different agents and helps solving problems that individual agents may face, e.g., occlusions and small sensing range. Prior methods usually separate the multi-agent fusion and multi-time fusion into two consecutive steps. In contrast, this paper proposes an efficient collaborative perception that aggregates the observations from different agents (space) and different times into a unified spatio-temporal space simultanesouly. The unified spatio-temporal space brings two benefits, i.e., efficient feature transmission and superior feature fusion. 1) Efficient feature transmission: each static object yields a single observation in the spatial temporal space, and thus only requires transmission only once (whereas prior methods re-transmit all the object features multiple times). 2) superior feature fusion: merging the multi-agent and multi-time fusion into a unified spatial-temporal aggregation enables a more holistic perspective, thereby enhancing perception performance in challenging scenarios. Consequently, our Collaborative perception with Spatio-temporal Transformer (CoST) gains improvement in both efficiency and accuracy. Notably, CoST is not tied to any specific method and is compatible with a majority of previous methods, enhancing their accuracy while reducing the transmission bandwidth.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 29 of its 42 references that are in the map. First posted on arXiv 1 Aug 2025.
Builds on
29 of 42 references.
References · 29
- 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
- 2020End-to-End Object Detection with Transformerscited by 7,414
- 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
- 2017CARLA: An Open Urban Driving Simulatorcited by 2,449
- 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,715
- 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,218
- 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 572
- 2022BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detectioncited by 341
- 2022V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformercited by 320
- 2023Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detectioncited by 315
- 2021OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communicationcited by 304
- 2020V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Predictioncited by 292
17 more
- 2022DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detectioncited by 273
- 2022Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Mapscited by 255
- 2022CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformerscited by 227
- 2022Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detectioncited by 178
- 2019F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Cloudscited by 171
- 2019Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Cloudscited by 165
- 2022Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusioncited by 162
- 2023V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perceptioncited by 155
- 2020Who2com: Collaborative Perception via Learnable Handshake Communicationcited by 127
- 2019Cooperative Perception for 3D Object Detection in Driving Scenarios using Infrastructure Sensorscited by 110
- 2022Latency-Aware Collaborative Perceptioncited by 86
- 2020DSDNet: Deep Structured self-Driving Networkcited by 62
- 2022Bridging the Domain Gap for Multi-Agent Perceptioncited by 60
- 2023Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perceptioncited by 38
- 2023Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detectioncited by 31
- 2023UMC: A Unified Bandwidth-efficient and Multi-resolution based Collaborative Perception Frameworkcited by 29
- 2023Select2Col: Leveraging Spatial-Temporal Importance of Semantic Information for Efficient Collaborative Perceptioncited by 12
Built on by
Citing papers per year: 2025: 2; 2026: 6.
8 papers.
- 2025SafeCoop: Unravelling Full Stack Safety in Agentic Collaborative Drivingcited by 2
- 2025JigsawComm: Joint Semantic Feature Encoding and Transmission for Communication-Efficient Cooperative Perceptioncited by 2
- 2026Linking Modality Isolation in Heterogeneous Collaborative Perceptioncited by 2
- 2026RC-GeoCP: Geometric Consensus for 4D Radar-Camera Collaborative Perceptioncited by 2
- 2026V2X-DSC: Multi-Agent Collaborative Perception with Distributed Source Coding Guided Communicationcited by 1
- 2026When the City Teaches the Car: Label-Free 3D Perception from Infrastructurecited by 0
- 2026CoAnchor: Robust Collaborative Perception under Spatio-Temporal Misalignment via Object-Level Anchorscited by 0
- 2026Multi-Source and Multi-Dimensional Information Fusion in Resource-Constrained Edge Networkscited by 0
- 2026Multi-Source and Multi-Dimensional Information Fusion in Resource-Constrained Edge Networks9 Oct 2026
- 2026CoAnchor: Robust Collaborative Perception under Spatio-Temporal Misalignment via Object-Level Anchors21 Aug 2026
- 2026When the City Teaches the Car: Label-Free 3D Perception from Infrastructure17 Mar 2026
- 2026RC-GeoCP: Geometric Consensus for 4D Radar-Camera Collaborative Perception28 Feb 2026
- 2026Linking Modality Isolation in Heterogeneous Collaborative Perception28 Feb 2026
- 2026V2X-DSC: Multi-Agent Collaborative Perception with Distributed Source Coding Guided Communication31 Jan 2026
- 2025JigsawComm: Joint Semantic Feature Encoding and Transmission for Communication-Efficient Cooperative Perception21 Nov 2025
- 2025SafeCoop: Unravelling Full Stack Safety in Agentic Collaborative Driving20 Oct 2025