自动驾驶

Long-range depth imaging using a single-photon detector array and non-local data fusion

Susan Chan, Abderrahim Halimi, Feng Zhu, Istvan Gyongy, Robert K. Henderson, Richard Bowman, Steve McLaughlin, Gerald S. Buller, Jonathan Leach

专题命中 多传感器融合 ：LiDAR(abstract)；分类 eess.IV

Semantic Road Layout Understanding by Generative Adversarial Inpainting

Lorenzo Berlincioni, Federico Becattini, Leonardo Galteri, Lorenzo Seidenari, Alberto Del Bimbo

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

Fusion of TanDEM-X and Cartosat-1 Elevation Data Supported by NeuralNetwork-Predicted Weight Maps

Hossein Bagheri, Michael Schmitt, Xiao Xiang Zhu

专题命中 多传感器融合 ：LiDAR(abstract)；分类 eess.IV

Comments This is the pre-acceptance version, to read the final version, please go to ISPRS Journal of Photogrammetry and Remote Sensing on ScienceDirect

Journal ref ISPRS Journal of Photogrammetry and Remote Sensing, Volume 144, October 2018, Pages 285-297

Improved Semantic Stixels via Multimodal Sensor Fusion

Florian Piewak, Peter Pinggera, Markus Enzweiler, David Pfeiffer, Marius Zöllner

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV

PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation

Danfei Xu, Dragomir Anguelov, Ashesh Jain

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV

Comments CVPR 2018

Online Temporal Calibration for Monocular Visual-Inertial Systems

Tong Qin, Shaojie Shen

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

Comments IROS 2018

Composite Kernel Local Angular Discriminant Analysis for Multi-Sensor Geospatial Image Analysis

Saurabh Prasad, Minshan Cui, Lifeng Yan

专题命中 多传感器融合 ：LiDAR(abstract)；分类 cs.CV

Calibrated Tree-Neural Fusion for Fine-Grained Vegetation Community Classification

用于细粒度植被群落分类的校准树神经融合

Dristi Datta, Md Khalid Hasan Sakib, Manoranjan Paul

机构 * School of Information Technology and Engineering, Sydney Metropolitan Institute of Technology (SydneyMet)（悉尼都会理工学院信息技术与工程学院） ； Department of Electrical & Electronic Engineering, Rajshahi University of Engineering & Technology（拉杰沙希工程技术大学电气与电子工程系） ； School of Computing, Mathematics and Engineering, Charles Sturt University（查尔斯·斯特尔特大学计算、数学与工程学院） 纠错

专题命中 多传感器融合 ：LiDAR(abstract)

AI总结 该研究针对植被群落分类问题，提出Calibrated EcoTreeFuseNet-Plus框架，结合多种方法进行融合，在小样本、细粒度生态分类中实现了可靠的判别校准权衡，取得较好准确率等指标且性能稳定。

Tensor Train Decomposition Based Noise Reduction and Enhanced Parameter Estimation for FMCW MIMO Radar Systems

基于张量列分解的FMCW MIMO雷达系统降噪与增强参数估计

Luoyan Zhu, Sergiy A. Vorobyov, Jie Wang, Yinsheng Liu, Zhangdui Zhong

专题命中 多传感器融合 ：autonomous driving(abstract)

AI总结 针对FMCW MIMO雷达在低信噪比下混合噪声干扰问题，提出基于张量列分解的框架，利用低秩结构和多维相关性进行噪声子空间分离，并通过数据平滑和旋转子空间算法实现距离、速度和角度参数的联合估计，显著提升信噪比和参数估计精度。

SoK: The Next Frontier in AV Security: Systematizing Perception Attacks and the Emerging Threat of Multi-Sensor Fusion

SoK：自动驾驶安全的下一个前沿：系统化感知攻击与多传感器融合的新兴威胁

Shahriar Rahman Khan, Tariqul Islam, Raiful Hasan

专题命中 多传感器融合 ：LiDAR(abstract)

AI总结 本文系统化分析了48篇关于自动驾驶感知层攻击的研究，揭示了从单传感器攻击到多传感器融合威胁的发展趋势，指出现有研究在现实测试、短期评估偏见及跨传感器一致性防御方面的不足，并提出融合感知安全的设计方向。

Comments 20 Pages, 3 figures

SAR/ISAR Imaging in 6G Network

SAR/ISAR成像在6G网络中的应用

Yanmo Hu, Shuowen Zhang, Ross Murch, Liang Liu

专题命中 多传感器融合 ：autonomous driving(abstract)

AI总结 本文提出两种高分辨率无线电成像方案，利用多普勒信息实现6G网络下的成像，无需范围估计，解决了带宽限制问题。

Obstacle Detection at Level Crossings under Adverse Weather Conditions -- A Survey

恶劣天气条件下铁路道口障碍物检测——综述

Chenyang Yan, Mats Bengtsson

专题命中 多传感器融合 ：LiDAR(abstract)

AI总结 本文综述了恶劣天气下铁路道口障碍物检测的传感器技术和融合策略，分析了各传感器的优缺点及应对措施，提出未来研究方向以提升检测系统的可靠性和适应性。

Multimodal Mixture-of-Experts for ISAC in Low-Altitude Wireless Networks

多模态专家混合模型用于低空无线网络中的ISAC

Kai Zhang, Wentao Yu, Hengtao He, Shenghui Song, Jun Zhang, Khaled B. Letaief

机构 * IEEE 纠错

专题命中 多传感器融合 ：LiDAR(abstract)

AI总结 本文提出了一种多模态专家混合模型，用于提升低空无线网络中ISAC的性能，通过自适应融合策略提高环境感知和通信效率。

Datasets for Valence and Arousal Inference: A Survey

Helen Schneider, Svetlana Pavlitska, Helen Gremmelmaier, J. Marius Zöllner

专题命中 多传感器融合 ：autonomous driving(abstract)

Comments Accepted for publication at ABAW Workshop at CVPR2025

A Hybrid Approach for Extending Automotive Radar Operation to NLOS Urban Scenarios

Aviran Gal, Igal Bilik

专题命中 多传感器融合 ：autonomous driving(abstract)

Comments Accepted in IEEE Transactions on Aerospace and Electronic Systems (Early Access)

Journal ref IEEE Trans. Aerosp. Electron. Syst., Early Access (2025)

Choice Outweighs Effort: Facilitating Complementary Knowledge Fusion in Federated Learning via Re-calibration and Merit-discrimination

Ming Yang, Dongrun Li, Xin Wang, Xiaoyang Yu, Xiaoming Wu, Shibo He

机构 * Key Lab. of Computing Power Network ； Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China ； Shandong Provincial Key Lab. of Industrial Network ； Information System Security, Shandong Fundamental Research Center for Computer Science, Jinan, China ； College of Control Science ； Engineering, Zhejiang University, Hangzhou, China 纠错

专题命中 多传感器融合 ：autonomous driving(abstract)

Multimodal Radio and Vision Fusion for Robust Localization in Urban V2I Communications

Can Zheng, Jiguang He, Chung G. Kang, Guofa Cai, Henk Wymeersch

专题命中 多传感器融合 ：autonomous driving(abstract)

Comments 6 pages, 6 figures, submitted to conference

High Resolution Millimeter Wave Imaging Based on FMCW Radar Systems at W-Band

Shahrokh Hamidi, M. R. Nezhad-Ahmadi

专题命中 多传感器融合 ：LiDAR(abstract)

Lessons Learned from the Real-World Deployment of Multi-Sensor Fusion for Proactive Work Zone Safety Application

Minhaj Uddin Ahmad, Sagar Dasgupta, Mizanur Rahman, Sakib Khan, Md Wasiul Haque, Suhala Rabab Saba, David Bodoh, Nathan Huynh, Li Zhao, Eren Erman Ozguven

专题命中 多传感器融合 ：LiDAR(abstract)

Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning

Ziyi Liang, Annie Qu, Babak Shahbaba

机构 * Department of Statistics, University of California, Irvine, CA, USA（统计学系，加州大学伊维奇分校） ； Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, USA（统计学与应用概率系，加州大学圣巴巴拉分校） 纠错

专题命中 多传感器融合 ：autonomous driving(abstract)

Multi-Modal Sensor Fusion for Proactive Blockage Prediction in mmWave Vehicular Networks

Ahmad M. Nazar, Abdulkadir Celik, Mohamed Y. Selim, Asmaa Abdallah, Daji Qiao, Ahmed M. Eltawil

机构 * Department of Electrical and Computer Engineering, Iowa State University of Science and Technology（电气与计算机工程系，爱荷华州立大学） ； Computer, Electrical, and Mathematical Sciences & Engineering (CEMSE) Division at King Abdullah University of Science and Technology (KAUST)（国王 Abdullah 科学与技术大学（KAUST）计算机、电气和数学科学与工程（CEMSE）系） 纠错

专题命中 多传感器融合 ：LiDAR(abstract)

Comments Accepted in IEEE Asilomar Conference on Signals, Systems, and Computers 2025

EV-STLLM: Electric vehicle charging forecasting based on spatio-temporal large language models with multi-frequency and multi-scale information fusion

Hang Fan, Yunze Chai, Chenxi Liu, Weican Liu, Zuhan Zhang, Wencai Run, Dunnan Liu

专题命中 多传感器融合 ：occupancy(abstract)

Chirp Delay-Doppler Domain Modulation: A New Paradigm of Integrated Sensing and Communication for Autonomous Vehicles

Zhuoran Li, Shufeng Tan, Zhen Gao, Yi Tao, Zhonghuai Wu, Zhongxiang Li, Chun Hu, Dezhi Zheng

专题命中 多传感器融合 ：autonomous driving(abstract)

Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion

Grigor Bezirganyan, Sana Sellami, Laure Berti-Équille, Sébastien Fournier

机构 * Aix-Marseille Univ（艾克斯-马赛大学） ； LIS（实验室） ； IRD（法国国家科研 Institute） ； ESPACE-DEV 纠错

专题命中 多传感器融合 ：autonomous driving(abstract)

Journal ref Proceedings of The 28th International Conference on Artificial Intelligence and Statistics 2025, in Proceedings of Machine Learning Research 258:3142-3150 Available from https://proceedings.mlr.press/v258/bezirganyan25a.html

What Would Trojans Do? Exploiting Partial-Information Vulnerabilities in Autonomous Vehicle Sensing

R. Spencer Hallyburton, Qingzhao Zhang, Z. Morley Mao, Michael Reiter, Miroslav Pajic

专题命中 多传感器融合 ：LiDAR(abstract)

Quantum Internet Use Case Analysis for the Automotive Industry

K. L. van der Enden, R. Kirschner, M. Krumtünger, A. Wilms

专题命中 多传感器融合 ：autonomous driving(abstract)

Comments 22 pages, 5 figures

A Review on Multisensor Data Fusion for Wearable Health Monitoring

Arlene John, Barry Cardiff, Deepu John

专题命中 多传感器融合 ：autonomous driving(abstract)

MUSIC-lite: Efficient MUSIC using Approximate Computing: An OFDM Radar Case Study

Rajat Bhattacharjya, Arnab Sarkar, Biswadip Maity, Nikil Dutt

专题命中 多传感器融合 ：autonomous driving(abstract)

Comments Paper accepted at ESWEEK-CASES 2024 as a Late Breaking (LB) Result paper. The definitive version of the work will appear in IEEE Embedded Systems Letters

DT-RaDaR: Digital Twin Assisted Robot Navigation using Differential Ray-Tracing

Sunday Amatare, Gaurav Singh, Raul Shakya, Aavash Kharel, Ahmed Alkhateeb, Debashri Roy

专题命中 多传感器融合 ：LiDAR(abstract)

Comments 15 pages, 25 figures, 7 tables, under review to IEEE transactions

Parallelized Instantaneous Velocity and Heading Estimation of Objects using Single Imaging Radar

Nihal Singh, Dibakar Sil, Ankit Sharma

专题命中 多传感器融合 ：autonomous driving(abstract)

Comments 6 pages, 6 figures, 2 tables. This work has been submitted to the IEEE for possible publication