自动驾驶

DRIFT: Dual-Representation Inter-Fusion Transformer for Automated Driving Perception with 4D Radar Point Clouds

DRIFT：双表示交叉融合变换器用于自动驾驶感知的4D雷达点云

Siqi Pei, Andras Palffy, Dariu M. Gavrila

机构 * Delft University of Technology（代尔夫特理工大学） ； Perciv AI 纠错

专题命中 多传感器融合 ：driving perception(title)；LiDAR(abstract)；分类 cs.RO、cs.CV

AI总结 DRIFT通过双路径架构融合局部和全局上下文信息，提升自动驾驶中4D雷达点云的感知性能，实现更准确的物体检测和道路估计。

LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model

LLM-MLFFN: 通过大语言模型的多级自动驾驶行为特征融合

Xiangyu Li, Tianyi Wang, Xi Cheng, Rakesh Chowdary Machineni, Zhaomiao Guo, Sikai Chen, Junfeng Jiao, Christian Claudel

机构 * Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin（德克萨斯大学奥斯汀分校土木、建筑与环境工程系） ； Systems Engineering Program, Cornell University（康奈尔大学系统工程项目） ； Department of Electrical and Computer Engineering, University of Michigan（密歇根大学电气与计算机工程系） ； Department of Civil and Environmental Engineering, University of Wisconsin-Madison（威斯康星大学麦迪逊分校土木与环境工程系） ； School of Architecture, The University of Texas at Austin（德克萨斯大学奥斯汀分校建筑学院） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.AI

AI总结 LLM-MLFFN通过大语言模型的多级特征融合提升自动驾驶行为分类的准确性和鲁棒性。

4D-CAAL: 4D Radar-Camera Calibration and Auto-Labeling for Autonomous Driving

4D-CAAL：面向自动驾驶的4D雷达-相机校准与自动标注

Shanliang Yao, Zhuoxiao Li, Runwei Guan, Kebin Cao, Meng Xia, Fuping Hu, Sen Xu, Yong Yue, Xiaohui Zhu, Weiping Ding, Ryan Wen Liu

机构 * School of Information Engineering, Yancheng Institute of Technology（信息工程学院，盐城职业技术学院） ； School of Navigation, Wuhan University of Technology（导航学院，武汉理工大学） ； The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州）） ； School of Information Engineering, Yancheng Institute Technology（信息工程学院，盐城职业技术学院） ； School of Advanced Technology, Xi’an Jiaotong-Liverpool University（先进技术学院，西安交通大学利物浦大学） ； School of Information Science and Technology, Nantong University（信息科学与技术学院，南通大学） ； State Key Laboratory of Maritime Technology and Safety（船舶技术与安全国家重点实验室） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.CV

AI总结 4D-CAAL提出了一种统一框架，通过双用途校准目标和自动标注流程，实现4D雷达与相机的高精度校准，减少人工标注工作量，加速自动驾驶多模态感知系统开发。

Advancing Autonomous Driving: DepthSense with Radar and Spatial Attention

推进自动驾驶：DepthSense与雷达与空间注意力

Muhamamd Ishfaq Hussain, Zubia Naz, Muhammad Aasim Rafique, Moongu Jeon

机构 * School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology（全州科学技术院电气工程与计算机科学学院） ； Division of National Science and Technology Data (Large Scale AI Research Group), Korea Institute of Science and Technology Information (KISTI)（国家科学技术数据 division（大规模人工智能研究组），韩国科学技术信息研究院） ； Department of Information Systems, College of Computer Sciences and Information Technology, King Faisal University（国王法尔萨大学信息系统系，计算机科学与信息科技学院） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.CV

AI总结 DepthSense通过结合雷达与单目相机数据，提升自动驾驶中的深度估计精度，采用编码器-解码器架构和空间注意力机制，实现高效且准确的深度感知。

Journal ref IEEE Sensors Journal 2025

Exploring Radar Data Representations in Autonomous Driving: A Comprehensive Review

Shanliang Yao, Runwei Guan, Zitian Peng, Chenhang Xu, Yilu Shi, Weiping Ding, Eng Gee Lim, Yong Yue, Hyungjoon Seo, Ka Lok Man, Jieming Ma, Xiaohui Zhu, Yutao Yue

机构 * School of Information Engineering, Yancheng Institute Technology（盐城理工学院信息工程学院） ； Thrust of Artificial Intelligence and Thrust of Intelligent Transportation, The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州）人工智能与智能交通研究所） ； Faculty of Science and Engineering, University of Liverpool（利物浦大学科学与工程学院） ； School of Advanced Technology, Xi’an Jiaotong-Liverpool University（西安交通大学利物浦大学高级技术学院） ； School of Information Science and Technology, Nantong University（南通大学信息科学与技术学院） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.CV、cs.AI

Comments Accepted by TITS

Journal ref IEEE Transactions on Intelligent Transportation Systems 2025

GS-LIVO: Real-Time LiDAR, Inertial, and Visual Multi-sensor Fused Odometry with Gaussian Mapping

Sheng Hong, Chunran Zheng, Yishu Shen, Changze Li, Fu Zhang, Tong Qin, Shaojie Shen

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV

FASIONAD : FAst and Slow FusION Thinking Systems for Human-Like Autonomous Driving with Adaptive Feedback

Kangan Qian, Zhikun Ma, Yangfan He, Ziang Luo, Tianyu Shi, Tianze Zhu, Jiayin Li, Jianhui Wang, Ziyu Chen, Xiao He, Yining Shi, Zheng Fu, Xinyu Jiao, Kun Jiang, Diange Yang, Takafumi Matsumaru

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.CV

Graph-Based Multi-Modal Sensor Fusion for Autonomous Driving

Depanshu Sani, Saket Anand

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.CV

Comments An extended abstract accepted at Young Researchers' Symposium, ICVGIP '24. This extended abstract contains the following: 1. Short summary of our work, SAGA-KF, accepted at ICPR'24. 2. A proposal that was awarded the Qualcomm Innovation Fellowship'24

Kaninfradet3D:A Road-side Camera-LiDAR Fusion 3D Perception Model based on Nonlinear Feature Extraction and Intrinsic Correlation

Pei Liu, Nanfang Zheng, Yiqun Li, Junlan Chen, Ziyuan Pu

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.CV、cs.AI

Efficient Fusion and Task Guided Embedding for End-to-end Autonomous Driving

Yipin Guo, Yilin Lang, Qinyuan Ren

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.AI

Comments Best Student Paper Award of the IEEE 13th Data-Driven Control and Learning Systems Conference

ASY-VRNet: Waterway Panoptic Driving Perception Model based on Asymmetric Fair Fusion of Vision and 4D mmWave Radar

Runwei Guan, Shanliang Yao, Xiaohui Zhu, Ka Lok Man, Yong Yue, Jeremy Smith, Eng Gee Lim, Yutao Yue

专题命中 多传感器融合 ：driving perception(title,abstract)；分类 cs.RO、cs.CV

Comments Accepted by IROS 2024

WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces

Shanliang Yao, Runwei Guan, Zhaodong Wu, Yi Ni, Zile Huang, Ryan Wen Liu, Yong Yue, Weiping Ding, Eng Gee Lim, Hyungjoon Seo, Ka Lok Man, Jieming Ma, Xiaohui Zhu, Yutao Yue

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.CV

Comments Accepted by IEEE Transactions on Intelligent Transportation Systems

Penalty-Based Imitation Learning With Cross Semantics Generation Sensor Fusion for Autonomous Driving

Hongkuan Zhou, Aifen Sui, Letian Shi, Yinxian Li

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.AI

Camera-LiDAR Fusion with Latent Contact for Place Recognition in Challenging Cross-Scenes

Yan Pan, Jiapeng Xie, Jiajie Wu, Bo Zhou

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV

Weakly Supervised Multi-Modal 3D Human Body Pose Estimation for Autonomous Driving

Peter Bauer, Arij Bouazizi, Ulrich Kressel, Fabian B. Flohr

专题命中 多传感器融合 ：autonomous driving(title)；LiDAR(abstract)；分类 cs.CV、cs.AI

Comments 7 pages, Accepted at IEEE-IV 2023

TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving

Lianqing Zheng, Zhixiong Ma, Xichan Zhu, Bin Tan, Sen Li, Kai Long, Weiqi Sun, Sihan Chen, Lu Zhang, Mengyue Wan, Libo Huang, Jie Bai

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.CV、cs.AI

Comments 2022 IEEE International Intelligent Transportation Systems Conference (ITSC 2022)

OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving

Guohang Yan, Liu Zhuochun, Chengjie Wang, Chunlei Shi, Pengjin Wei, Xinyu Cai, Tao Ma, Zhizheng Liu, Zebin Zhong, Yuqian Liu, Ming Zhao, Zheng Ma, Yikang Li

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.RO、cs.CV

Comments 16 pages, 31 figures

Improved Radar Localization on Lidar Maps Using Shared Embedding

Huan Yin, Yue Wang, Rong Xiong

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV

Comments Extended abstract. Spotlight Talk at Radar Perception for All-Weather Autonomy Workshop of ICRA 2021

Radar Camera Fusion via Representation Learning in Autonomous Driving

Xu Dong, Binnan Zhuang, Yunxiang Mao, Langechuan Liu

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.CV、cs.AI

Journal ref In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 1672-1681. 2021

Robust Autonomous Landing of UAV in Non-Cooperative Environments based on Dynamic Time Camera-LiDAR Fusion

Lyujie Chen, Xiaming Yuan, Yao Xiao, Yiding Zhang, Jihong Zhu

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV

Comments Submitted to ICRA 2021

A Sensitivity Analysis Approach for Evaluating a Radar Simulation for Virtual Testing of Autonomous Driving Functions

Anthony Ngo, Max Paul Bauer, Michael Resch

专题命中 多传感器融合 ：autonomous driving(title)；LiDAR(abstract)；分类 cs.RO、cs.CV

Comments IEEE 2020 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS 2020)

Camera-Lidar Integration: Probabilistic sensor fusion for semantic mapping

Julie Stephany Berrio, Mao Shan, Stewart Worrall, Eduardo Nebot

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV

Comments 15 pages. arXiv admin note: text overlap with arXiv:2003.01871

Semantic sensor fusion: from camera to sparse lidar information

Julie Stephany Berrio, Mao Shan, Stewart Worrall, James Ward, Eduardo Nebot

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV

Comments 8 pages, this paper was submitted to ITSC 2020

Robust Fusion of LiDAR and Wide-Angle Camera Data for Autonomous Mobile Robots

Varuna De Silva, Jamie Roche, Ahmet Kondoz

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV

LiDAR and Camera Calibration using Motion Estimated by Sensor Fusion Odometry

Ryoichi Ishikawa, Takeshi Oishi, Katsushi Ikeuchi

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.RO、cs.CV

Edge-Assisted Multimodal UAV Localization with Resource-Efficient Compression and Robust Fusion

基于资源高效压缩和鲁棒融合的边缘辅助多模态无人机定位

Zhong Ye, Yinghui He, Guanding Yu, Pavel Loskot

专题命中 多传感器融合 ：LiDAR(summary_cn,abstract)

AI总结 设计多模态无人机定位框架，利用相机、LiDAR和雷达传感模态。通过信息瓶颈压缩等模块应对传感节点资源有限、数据差异大及模态数据退化缺失等挑战，实验表明该框架能准确可靠定位无人机。

CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception

Youngseok Kim, Juyeb Shin, Sanmin Kim, In-Jae Lee, Jun Won Choi, Dongsuk Kum

专题命中 多传感器融合 ：autonomous driving(abstract)；BEV(abstract)；LiDAR(abstract)；分类 cs.RO、cs.CV、cs.AI

Comments IEEE/CVF International Conference on Computer Vision (ICCV'23). Code is available at https://github.com/youngskkim/CRN

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping

Tiago de Conto, John Armston, Ralph Dubayah

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.CV

CLIFE: Camera-LiDAR Fusion Framework for Edge-Deployable Roadside VRU Perception

CLIFE：用于边缘可部署路边VRU感知的相机-激光雷达融合框架

Tam Bang, Hoang H. Nguyen, Lei Cheng, Lihao Guo, Siyang Cao, Hussam Abubakr, Tianya Zhang, Austin Harris, Mina Sartipi

专题命中 多传感器融合 ：LiDAR(title,abstract)；分类 cs.CV

AI总结 针对路边VRU感知难题，提出CLIFE框架，集成无目标在线校准与轻量级后期融合跟踪于单嵌入式设备，无需云卸载。经实验验证，该框架提升了传感器感知能力与鲁棒性，核心运行高效，为下游安全应用提供基础并减少相关开销。

Comments Accepted for publication at the 2026 IEEE 29th International Conference on Intelligent Transportation Systems (ITSC 2026). 8 pages, 7 figures

LLM-Empowered Multimodal Fusion Framework for Autonomous Driving: Semantic Enhancement and Channel-Adaptive Design

LLM赋能的自动驾驶多模态融合框架：语义增强与信道自适应设计

Wen Wang, Yaping Sun, Yejun He, Hao Chen, Zhiyong Chen, Xiaodong Xu, Nan Ma, Shuguang Cui

机构 * National Natural Science Foundation of China（国家自然科学基金） ； Shenzhen Natural Science Foundation（深圳市自然科学基金） ； Shenzhen Key Laboratory Evaluation（深圳市重点实验室评估） 纠错

专题命中 多传感器融合 ：autonomous driving(title,abstract)；分类 cs.CV

AI总结 提出LM-SCIP框架，以LLM为核心推理中枢，通过信道自适应语义模块动态融合视觉与雷达特征，实现低信噪比下的视觉主导回退和高信噪比下的协同融合，在nuScenes和VIRAT数据集上显著提升定位精度。

Comments 6 pages, 4 figures. Accepted by 2026 IEEE 37th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)