mlsanityData to 7 Oct 2026

Rethinking the Role of Infrastructure in Collaborative Perception

arXiv 2410.11259 ↗First posted 15 Oct 2024cs.CVcited by 3

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Abstract (arXiv)

Collaborative Perception (CP) is a process in which an ego agent receives and fuses sensor information from surrounding vehicles and infrastructure to enhance its perception capability. To evaluate the need for infrastructure equipped with sensors, extensive and quantitative analysis of the role of infrastructure data in CP is crucial, yet remains underexplored. To address this gap, we first quantitatively assess the importance of infrastructure data in existing vehicle-centric CP, where the ego agent is a vehicle. Furthermore, we compare vehicle-centric CP with infra-centric CP, where the ego agent is now the infrastructure, to evaluate the effectiveness of each approach. Our results demonstrate that incorporating infrastructure data improves 3D detection accuracy by up to 10.30%, and infra-centric CP shows enhanced noise robustness and increases accuracy by up to 46.47% compared with vehicle-centric CP.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 20 of its 34 references that are in the map. First posted on arXiv 15 Oct 2024.

Builds on

20 of 34 references.

References · 20

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8 more
  1. 2023Collaborative Perception in Autonomous Driving: Methods, Datasets and Challengescited by 87
  2. 2024An Extensible Framework for Open Heterogeneous Collaborative Perceptioncited by 87
  3. 2023BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detectioncited by 74
  4. 2023Spatio-Temporal Domain Awareness for Multi-Agent Collaborative Perceptioncited by 52
  5. 2023CORE: Cooperative Reconstruction for Multi-Agent Perceptioncited by 41
  6. 2022PillarGrid: Deep Learning-based Cooperative Perception for 3D Object Detection from Onboard-Roadside LiDARcited by 25
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  8. 2024ParCon: Noise-Robust Collaborative Perception via Multi-module Parallel Connectioncited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025A Survey on Deep Multi-Task Learning in Connected Autonomous Vehiclescited by 0
  2. 2026HyDRA: Hybrid Domain-Aware Robust Architecture for Heterogeneous Collaborative Perceptioncited by 0
  3. 2026Adaptation-Free Heterogeneous Collaborative Perception with Unseen Agent Configurationscited by 0