When2com: Multi-Agent Perception via Communication Graph Grouping
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Abstract (arXiv)
While significant advances have been made for single-agent perception, many applications require multiple sensing agents and cross-agent communication due to benefits such as coverage and robustness. It is therefore critical to develop frameworks which support multi-agent collaborative perception in a distributed and bandwidth-efficient manner. In this paper, we address the collaborative perception problem, where one agent is required to perform a perception task and can communicate and share information with other agents on the same task. Specifically, we propose a communication framework by learning both to construct communication groups and decide when to communicate. We demonstrate the generalizability of our framework on two different perception tasks and show that it significantly reduces communication bandwidth while maintaining superior performance.
Key facts. Cited by 157 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 May 2020.
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Citing papers per year: 2021: 9; 2022: 11; 2023: 31; 2024: 33; 2025: 40; 2026: 33.
157 papers.
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- 2021Learning Distilled Collaboration Graph for Multi-Agent Perceptioncited by 194
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- 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
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- 2026Emergent Specialization in Populations of Self-Supervised Collaborative Vision Experts Without a Shared Gate or Cross-Agent Gradients29 Sep 2026
- 2026Embodied Semantic Communication for Collective Autonomous Agents: A Tutorial on Representation, Wireless Delivery, and Closed-Loop Coordination28 Sep 2026
- 2026SemRD-V2X: Closure-Guided Communication with Bounded Inference for Cooperative Perception28 Sep 2026
- 2026Latent Telepathy: Multi-Robot Communication with Self-Supervised Perceptual Latents20 Sep 2026
- 2026CoAdapt: An LLM-based Framework for Adaptive Collaborative Perception in IIoT Robotic Swarms15 Sep 2026
- 2026CauseCollab: Causal Unified and Modality-Agnostic Network for Heterogeneous Collaborative Perception3 Sep 2026
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