English(EN) QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception

QuantV2X系统在车辆感知方面实现3.2倍低延迟

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-29 04:00

研究人员推出QuantV2X，一个新颖的多智能体系统，专为车辆高效协同感知而设计。该系统对神经网络模型和传输消息进行全量化处理，显著降低了计算和传输成本，同时不牺牲准确性。与全精度系统相比，QuantV2X实现了3.2倍的系统级延迟降低和mAP30的显著提升，使其更适合实时、资源受限的环境。 AI

影响为实时车辆感知实现更高效、可部署的AI系统。

排序理由介绍新系统和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Seth Z. Zhao, Huizhi Zhang, Zhaowei Li, Juntong Peng, Anthony Chui, Zewei Zhou, Zonglin Meng, Hao Xiang, Zhiyu Huang, Fujia Wang, Ran Tian, Chenfeng Xu, Bolei Zhou, Jiaqi Ma · 2026-06-29 04:00

QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception

arXiv:2509.03704v2 Announce Type: replace Abstract: Cooperative perception through Vehicle-to-Everything (V2X) communication offers significant potential for enhancing vehicle perception by mitigating occlusions and expanding the field of view. However, past research has predomin…