arXivDaily arXiv每日学术速递 周一至周五更新

视觉与机器人

自动驾驶

自动驾驶感知、规划、BEV、占用预测、激光雷达和仿真评测。

2026-01-30 至 2026-01-30 共收录 3 信号源:cs.RO, cs.CV, eess.IV, cs.AI

1. 感知 3 篇

2512.08557 2026-01-30 cs.CV 79%

SSCATeR: Sparse Scatter-Based Convolution Algorithm with Temporal Data Recycling for Real-Time 3D Object Detection in LiDAR Point Clouds

SSCATeR: 基于稀疏散射的卷积算法与时间数据回收用于LiDAR点云中的实时3D物体检测

Alexander Dow, Manduhu Manduhu, Matheus Santos, Ben Bartlett, Gerard Dooly, James Riordan

机构 * Drone Systems Lab, School of Computing, Engineering and Physical Sciences, University of the West of Scotland(无人机系统实验室,计算、工程与物理科学学院,西方苏格兰大学) Centre for Robotics and Intelligent Systems, University of Limerick(机器人与智能系统中心,利默里克大学)

专题命中 感知 :LiDAR(title,abstract);分类 cs.CV

AI总结 SSCATeR通过时间数据回收和稀疏散射卷积,实现LiDAR点云中实时3D物体检测的高效检测。

Comments 23 Pages, 27 Figures, This work has been accepted for publication by the IEEE Sensors Journal. Please see the first page of the article PDF for copyright information

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2601.12142 2026-01-30 eess.AS cs.MM cs.RO 79%

Listen, Look, Drive: Coupling Audio Instructions for User-aware VLA-based Autonomous Driving

Listen, Look, Drive: 通过用户意识的VLA基于自主驾驶的音频指令耦合

Ziang Guo, Feng Yang, Xuefeng Zhang, Jiaqi Guo, Kun Zhao, Yixiao Zhou, Peng Lu, Sifa Zheng, Zufeng Zhang

机构 * SuZhou Automotive Research Institute of Tsinghua University(清华大学苏州汽车研究院) Department of Electrical and Electronic Engineering, The University of Hong Kong(香港大学电子与电气工程系) Hyundai Motor Advanced Tech. R&D Center School of Vehicle and Mobility, Tsinghua University(清华大学车辆与移动系统学院)

专题命中 感知 :autonomous driving(title,abstract);分类 cs.RO

AI总结 EchoVLA通过结合音频指令与视觉信息,提升自动驾驶对用户意图和情绪的感知能力,显著降低误差和碰撞率。

Comments Accepted by IV

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2501.13518 2026-01-30 cs.CV 57%

Text-driven Online Action Detection

基于文本的在线动作检测

Manuel Benavent-Lledo, David Mulero-Pérez, David Ortiz-Perez, Jose Garcia-Rodriguez

机构 * Department of Computer Technology, University of Alicante(阿拉维大学计算机技术系) ValgrAI - Valencian Graduate School and Research Network of Artificial Intelligence(瓦伦西亚人工智能研究生学校和研究网络) Institute of Informatics Research, University of Alicante(阿拉维大学信息研究所)

专题命中 感知 :autonomous driving(abstract);分类 cs.CV

AI总结 本文提出TOAD模型,利用CLIP文本嵌入实现高效的零样本和少样本在线动作检测,其在THUMOS14数据集上的mAP达到82.46%

Comments Published in Integrated Computer-Aided Engineering

Journal ref Integrated Computer-Aided Engineering. 2025;32(4):415-423

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