多模态信息融合

M2DA: Multi-Modal Fusion Transformer Incorporating Driver Attention for Autonomous Driving

Dongyang Xu, Haokun Li, Qingfan Wang, Ziying Song, Lei Chen, Hanming Deng

专题命中 自动驾驶多传感器融合 ：multi-modal fusion(title,abstract)；分类 cs.CV、cs.RO

Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer

Hao Shao, Letian Wang, RuoBing Chen, Hongsheng Li, Yu Liu

专题命中 自动驾驶多传感器融合 ：sensor fusion(title,abstract)；分类 cs.CV、cs.RO

Comments Accepted at CoRL 2022

TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving

Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, Andreas Geiger

专题命中 自动驾驶多传感器融合 ：sensor fusion(title,abstract)；分类 cs.CV、cs.RO

Comments arXiv admin note: text overlap with arXiv:2104.09224

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration

端到端3D时空感知与多模态融合及V2X协作

Zhenwei Yang, Yibo Ai, Weidong Zhang

机构 * National Center for Materials Service Safety（材料服务安全国家中心） ； University of Science and Technology Beijing（北京科技大学） 纠错

专题命中 自动驾驶多传感器融合 ：multimodal fusion(title,abstract)；分类 cs.CV

AI总结 XET-V2X通过多模态融合与V2X协作，实现端到端3D时空感知，提升复杂交通场景下的检测与跟踪性能。

Comments 21 pages, 10 figures

Journal ref IEEE Internet of Things Journal, vol. 13, no. 15, pp. 33456-33475, 1 Aug.1, 2026

CAMF-Det: Closure-Aware Multimodal Fusion for LiDAR-Camera 3D Object Detection on UAV Platforms

CAMF-Det: 面向无人机平台的激光雷达-相机闭合感知多模态融合3D目标检测

Yanze Jiang, Yanfeng Gu, Xian Li

机构 * School of Electronics and Information Engineering, Harbin Institute of Technology（哈尔滨工业大学电子与信息工程学院） 纠错

专题命中 自动驾驶多传感器融合 ：multimodal fusion(title,abstract)；分类 cs.CV

AI总结 针对无人机俯视场景中树冠遮挡导致的多模态信息退化问题，提出基于比尔-朗伯定律的闭合感知融合框架CAMF-Det，通过显式建模双模态遮挡强度并注入检测流程，在自建数据集上实现困难级别mAP_BEV提升9.43%和4.88%。

Multi-Modal Sensor Fusion using Hybrid Attention for Autonomous Driving

多模态传感器融合使用混合注意力用于自动驾驶

Mayank Mayank, Bharanidhar Duraisamy, Florian Geiß, Abhinav Valada

机构 * Mercedes-Benz AG（梅赛德斯-奔驰集团） ； University of Freiburg（弗莱堡大学） 纠错

专题命中 自动驾驶多传感器融合 ：sensor fusion(title)；hybrid fusion(abstract)；分类 cs.CV

AI总结 本文提出MMF-BEV框架，通过变形注意力实现雷达与摄像头BEV融合，通过传感器贡献分析验证传感器互补性，并在VoD数据集上优于单模态基线。

Comments 9 pages, 8 figures

DriveAgent: Multi-Agent Structured Reasoning with LLM and Multimodal Sensor Fusion for Autonomous Driving

Xinmeng Hou, Wuqi Wang, Long Yang, Hao Lin, Jinglun Feng, Haigen Min, Xiangmo Zhao

机构 * Chang’an University（长安大学） ； Agency for Science, Technology and Research (A*STAR)（科技研究局） ； University of California, Davis（加州大学戴维斯分校） ； CCNY Robotics Lab, The City College of New York（纽约城市学院机器人实验室） 纠错

专题命中 自动驾驶多传感器融合 ：sensor fusion(title,abstract)；分类 cs.RO

Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving

Yang Lou, Qun Song, Qian Xu, Rui Tan, Jianping Wang

专题命中 自动驾驶多传感器融合 ：multi-modal fusion(title,abstract)；分类 cs.CV

Comments In proceedings of the 26th European Conference on Artificial Intelligence ECAI 2023. 8 pages + 2 appendix pages

Fisheye Camera and Ultrasonic Sensor Fusion For Near-Field Obstacle Perception in Bird's-Eye-View

Arindam Das, Sudarshan Paul, Niko Scholz, Akhilesh Kumar Malviya, Ganesh Sistu, Ujjwal Bhattacharya, Ciarán Eising

专题命中 自动驾驶多传感器融合 ：sensor fusion(title)；multimodal fusion(abstract)；分类 cs.CV

Comments 16 pages, 12 Figures, 6 tables

LeTFuser: Light-weight End-to-end Transformer-Based Sensor Fusion for Autonomous Driving with Multi-Task Learning

Pedram Agand, Mohammad Mahdavian, Manolis Savva, Mo Chen

专题命中 自动驾驶多传感器融合 ：sensor fusion(title,abstract)；分类 cs.CV

Comments 11 pages, 2 figures, 3 tables. CVPR Workshops (VCAD). 2023

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 自动驾驶多传感器融合 ：sensor fusion(title,abstract)；分类 cs.RO

Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression

Felix Ott, Nisha Lakshmana Raichur, David Rügamer, Tobias Feigl, Heiko Neumann, Bernd Bischl, Christopher Mutschler

专题命中 自动驾驶多传感器融合 ：multimodal fusion(title,abstract)；分类 cs.CV

Comments Under review

RealNet: Combining Optimized Object Detection with Information Fusion Depth Estimation Co-Design Method on IoT

Zhuohao Li, Fandi Gou, Qixin De, Leqi Ding, Yuanhang Zhang, Yunze Cai

专题命中 自动驾驶多传感器融合 ：information fusion(title,abstract)；分类 cs.CV

FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detection

Shaoqing Xu, Dingfu Zhou, Jin Fang, Junbo Yin, Zhou Bin, Liangjun Zhang

专题命中 自动驾驶多传感器融合 ：multimodal fusion(title,abstract)；分类 cs.CV

Comments Accepted by ITSC 2021

Attention-based Multi-modal Fusion Network for Semantic Scene Completion

Siqi Li, Changqing Zou, Yipeng Li, Xibin Zhao, Yue Gao

专题命中 自动驾驶多传感器融合 ：multi-modal fusion(title,abstract)；分类 cs.CV

Comments Accepted by AAAI 2020

Large-Scale Traffic Congestion Prediction based on Multimodal Fusion and Representation Mapping

Bodong Zhou, Jiahui Liu, Songyi Cui, Yaping Zhao

专题命中 自动驾驶多传感器融合 ：multimodal fusion(title,abstract)

Journal ref 2022 IEEE International Conference on Data Science and Advanced Analytics

Research on Self-adaptive Online Vehicle Velocity Prediction Strategy Considering Traffic Information Fusion

Ziyan Zhang, Junhao Shen, Dongwei Yao, Feng Wu

专题命中 自动驾驶多传感器融合 ：information fusion(title,abstract)

Comments 9 pages, 7 figures

ODIN: Obfuscation-based privacy preserving consensus algorithm for Decentralized Information fusion in smart device Networks

Moreno Ambrosin, Paolo Braca, Mauro Conti, Riccardo Lazzaretti

专题命中 自动驾驶多传感器融合 ：information fusion(title,abstract)

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 自动驾驶多传感器融合 ：multimodal fusion(title)；分类 cs.CV、eess.SP

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)

BEVDilation: LiDAR-Centric Multi-Modal Fusion for 3D Object Detection

BEVDilation：以LiDAR为中心的多模态融合用于3D目标检测

Guowen Zhang, Chenhang He, Liyi Chen, Lei Zhang

专题命中 自动驾驶多传感器融合 ：multi-modal fusion(title)；分类 cs.CV、cs.RO

AI总结 BEVDilation提出以LiDAR为中心的多模态融合方法，通过稀疏体素扩张和语义引导BEV扩张模块提升3D目标检测性能，有效缓解深度误差带来的空间错位问题。

Comments Accept by AAAI26

3DTTNet: Multimodal Fusion-Based 3D Traversable Terrain Modeling for Off-Road Environments

Zitong Chen, Chao Sun, Shida Nie, Chen Min, Changjiu Ning, Haoyu Li, Bo Wang

机构 * Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen（深圳汽车研究院，北京理工大学，深圳） ； School of Mechanical Engineering, Beijing Institute of Technology, Beijing（机械工程学院，北京理工大学，北京） ； Research Center for Intelligent Computing Systems, Institute of Computing Technology, Chinese Academy of Sciences, Beijing（智能计算系统研究中心，计算技术研究所，中国科学院，北京） 纠错

专题命中 自动驾驶多传感器融合 ：multimodal fusion(title)；分类 cs.CV、cs.RO

Comments 15 pages,13 figures

Advancing Autonomous Driving Perception: Analysis of Sensor Fusion and Computer Vision Techniques

Urvishkumar Bharti, Vikram Shahapur

专题命中 自动驾驶多传感器融合 ：sensor fusion(title)；分类 cs.CV、cs.RO

Comments 7 pages

Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object Segmentation

Jiadai Sun, Yuchao Dai, Xianjing Zhang, Jintao Xu, Rui Ai, Weihao Gu, Xieyuanli Chen

专题命中 自动驾驶多传感器融合 ：information fusion(title)；分类 cs.CV、cs.RO

Comments Accepted by IROS2022. Code: https://github.com/haomo-ai/MotionSeg3D

MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction

Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S. Refaat, Nigamaa Nayakanti, Andre Cornman, Kan Chen, Bertrand Douillard, Chi Pang Lam, Dragomir Anguelov, Benjamin Sapp

专题命中 自动驾驶多传感器融合 ：information fusion(title)；分类 cs.CV、cs.RO

Integrating Multi-Modal Sensors: A Review of Fusion Techniques for Intelligent Vehicles

多模态传感器整合：智能车辆融合技术综述

Chuheng Wei, Ziye Qin, Ziyan Zhang, Guoyuan Wu, Matthew J. Barth

机构 * College of Engineering, Center for Environmental Research and Technology, University of California at Riverside（工程学院、环境研究与技术中心、加州大学河滨分校） ； School of Transportation and Logistics, Southwest Jiaotong University（交通运输与物流学院、西南交通大学） 纠错

专题命中 自动驾驶多传感器融合 ：sensor fusion(abstract)；multi-sensor fusion(abstract)；分类 cs.CV、cs.RO、cs.MM

AI总结 本文综述了多传感器融合技术在自动驾驶中的应用，分析了深度学习方法、多模态数据集及新兴趋势，强调了其提升系统适应性和鲁棒性的潜力。

Comments Accepted by IEEE IV 2025

Journal ref Proceedings of the 2025 IEEE Intelligent Vehicles Symposium (IV), pp. 1817-1824, 2025

AG-Fusion: adaptive gated multimodal fusion for 3d object detection in complex scenes

Sixian Liu, Chen Xu, Qiang Wang, Donghai Shi, Yiwen Li

机构 * Yaowu Technology Co., Ltd, Shenzhen, China（深圳优华科技有限公司，深圳，中国） 纠错

专题命中 自动驾驶多传感器融合 ：multimodal fusion(title)；分类 cs.CV

Contrastive Learning-Driven Traffic Sign Perception: Multi-Modal Fusion of Text and Vision

Qiang Lu, Waikit Xiu, Xiying Li, Shenyu Hu, Shengbo Sun

机构 * School of Intelligent Systems Engineering, Sun Yat-sen University（中山大学智能系统工程学院） ； Guangdong Provincial Key Laboratory of Intelligent Transportation System（广东省智能交通系统重点实验室） 纠错

专题命中 自动驾驶多传感器融合 ：multi-modal fusion(title)；分类 cs.CV

Comments 11pages, 5 figures

KAN-RCBEVDepth: A multi-modal fusion algorithm in object detection for autonomous driving

Zhihao Lai, Chuanhao Liu, Shihui Sheng, Zhiqiang Zhang

专题命中 自动驾驶多传感器融合 ：multi-modal fusion(title)；分类 cs.CV

RadSegNet: A Reliable Approach to Radar Camera Fusion

Kshitiz Bansal, Keshav Rungta, Dinesh Bharadia

专题命中 自动驾驶多传感器融合 ：radar camera fusion(title)；分类 cs.CV

Enabling Efficient Deep Convolutional Neural Network-based Sensor Fusion for Autonomous Driving

Xiaoming Zeng, Zhendong Wang, Yang Hu

专题命中 自动驾驶多传感器融合 ：sensor fusion(title)；分类 cs.CV