English(EN) UFMF: Radar-Guided Kinematic Priors for Real-Time 4D Occupancy Forecasting

UFMF系统使用雷达进行实时4D占用预测

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

研究人员开发了UFMF，一个新颖的、用于自动驾驶的实时4D占用预测系统。该系统利用无注意力的时间核心结合雷达引导的运动先验，即使在高速度和长视界下也能准确预测参与者的运动。与现有的世界模型相比，UFMF在nuScenes数据集上取得了卓越的性能，同时计算成本显著降低。 AI

影响为自动驾驶系统提供更高效、更准确的周围参与者运动实时预测。

排序理由这是一篇详细介绍用于4D占用预测新系统的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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本文如何被排名

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arXiv cs.CV TIER_1 English(EN) · Zeping Zhang, Zhuoya Zhao, Robert Lagani\`ere · 2026-11-02 05:00

UFMF: Radar-Guided Kinematic Priors for Real-Time 4D Occupancy Forecasting

arXiv:2610.40947v1 Announce Type: new Abstract: Real-time 4D occupancy forecasting requires reliably extrapolating both ego motion and surrounding actor motion under strict latency budgets. Recent occupancy world models improve long-horizon fidelity through generative decoders an…