为自动驾驶提供具有可扩展连接时序关系的雷达感知能力

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2024-04-14 DOI:10.1109/icassp48485.2024.10446449

Ryoma Yataka, Pu Wang, P. Boufounos, Ryuhei Takahashi

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引用次数: 0

摘要

由于汽车雷达数据的噪声和空间分辨率较低，探索连续 2 个雷达帧的可学习特征的时间关系已显示出在下游任务中的性能增益（e

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Radar Perception with Scalable Connective Temporal Relations for Autonomous Driving

Due to the noise and low spatial resolution in automotive radar data, exploring temporal relations of learnable features over consecutive 2 radar frames has shown performance gain on downstream tasks (e

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ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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