自动驾驶

Towards Compact Autonomous Driving Perception with Balanced Learning and Multi-sensor Fusion

面向紧凑型自动驾驶感知的平衡学习与多传感器融合

Oskar Natan, Jun Miura

机构 * Department of Computer Science and Engineering, Toyohashi University of Technology（计算机科学与工程系，丰田寺大学） ； Department of Computer Science and Electronics, Gadjah Mada University（计算机科学与电子系，加查马达大学） 纠错

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

AI总结 提出一种紧凑的深度多任务学习模型，通过自适应损失加权和中间传感器融合技术，在单次前向传播中同时处理语义分割、深度估计、激光雷达分割和鸟瞰投影，实现高效自动驾驶感知。

Comments This work has been accepted for publication in IEEE Transactions on Intelligent Transportation Systems. https://ieeexplore.ieee.org/document/9712213

LRFusionPR: A Polar BEV-Based LiDAR-Radar Fusion Network for Place Recognition

Zhangshuo Qi, Luqi Cheng, Zijie Zhou, Guangming Xiong

机构 * Beijing Institute of Technology（北京理工大学） 纠错

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

Comments Accepted by IEEE Robotics and Automation Letters (RAL) 2025

Horizon3D: Sparse Radar-Camera Fusion for Long-Range 3D Perception in Autonomous Driving

Horizon3D: 用于自动驾驶远距离3D感知的稀疏雷达-相机融合

Geonho Bang, Geunju Baek, Dongyoung Lee, Wonjun Jeong, Jun Won Choi

机构 * Seoul National University（首尔大学） 纠错

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

AI总结 提出Horizon3D框架，通过高斯原语与稀疏BEV特征融合，结合双路径时序融合，实现远距离雷达-相机3D检测，在TruckScenes上达到SOTA性能。

Comments Accepted to ECCV 2026. Project page: https://geonhobang.github.io/horizon3d-project-page. Code: https://github.com/geonhobang/ECCV2026_Horizon3D

LRC-WeatherNet: LiDAR, RADAR, and Camera Fusion Network for Real-time Weather-type Classification in Autonomous Driving

LRC-WeatherNet：用于自动驾驶中实时天气类型分类的激光雷达、雷达和摄像头融合网络

Nour Alhuda Albashir, Lars Pernickel, Danial Hamoud, Idriss Gouigah, Eren Erdal Aksoy

机构 * Halmstad University, School of Information Technology, Center for Applied Intelligent Systems Research（哈姆斯塔德大学，信息科技学院，应用智能系统研究中心） 纠错

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

AI总结 本文提出LRC-WeatherNet，通过融合激光雷达、雷达和摄像头数据，实现在恶劣天气下的实时天气分类，优于单一传感器基线，且在MSU-4S数据集上表现优异。

Comments Accepted for publication at IEEE Intelligent Vehicles Symposium - IVS 2026

CLFT: Camera-LiDAR Fusion Transformer for Semantic Segmentation in Autonomous Driving

Junyi Gu, Mauro Bellone, Tomáš Pivoňka, Raivo Sell

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

Comments Accepted to IEEE Transactions on Intelligent Vehicles

Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving

Bo Yang, Xiaoyu Ji, Zizhi Jin, Yushi Cheng, Wenyuan Xu

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

FlatFusion: Delving into Details of Sparse Transformer-based Camera-LiDAR Fusion for Autonomous Driving

Yutao Zhu, Xiaosong Jia, Xinyu Yang, Junchi Yan

机构 * School of Computer Science and School of Artificial Intelligence, Shanghai Jiao Tong University（计算机科学学院和人工智能学院，上海交通大学） ； Carnegie Mellon University（卡内基梅隆大学） 纠错

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

Comments Accepted by ICRA 2025

CLONeR: Camera-Lidar Fusion for Occupancy Grid-aided Neural Representations

Alexandra Carlson, Manikandasriram Srinivasan Ramanagopal, Nathan Tseng, Matthew Johnson-Roberson, Ram Vasudevan, Katherine A. Skinner

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

Comments first two authors equally contributed

Journal ref IEEE Robotics and Automation Letters, vol. 8, no. 5, pp. 2812-2819, May 2023

Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks

Yulong Cao*, Ningfei Wang*, Chaowei Xiao*, Dawei Yang*, Jin Fang, Ruigang Yang, Qi Alfred Chen, Mingyan Liu, Bo Li

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

Comments Accepted by IEEE S&P 2021

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

Xiaoshuai Hao, Guanqun Liu, Yuting Zhao, Yuheng Ji, Mengchuan Wei, Haimei Zhao, Lingdong Kong, Rong Yin, Yu Liu

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

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 多传感器融合 ：autonomous driving(title,abstract)；LiDAR(abstract)；end-to-end driving(abstract)；分类 cs.RO、cs.CV、cs.AI

Comments arXiv admin note: text overlap with arXiv:2104.09224

DeepIPCv3: Event-Aware Multi-Modal Sensor Fusion for Sudden Pedestrian Crossing Avoidance

DeepIPCv3: 面向突发行人穿越避让的事件感知多模态传感器融合

Oskar Natan, Andi Dharmawan, Aufaclav Zatu Kusuma Frisky, Jazi Eko Istiyanto, Jun Miura

机构 * Department of Computer Science and Electronics, Universitas Gadjah Mada（计算机科学与电子系，加雅马达大学） ； Department of Computer Science and Engineering, Toyohashi University of Technology（计算机科学与工程系，东福士大学） 纠错

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

AI总结 提出DeepIPCv3框架，通过Transformer交叉模态注意力融合LiDAR点云与DVS事件流，实现突发行人穿越场景下的高反应性避让，在自定义多模态数据集上达到最优轨迹与控制精度。

DAOcc: 3D Object Detection Assisted Multi-Sensor Fusion for 3D Occupancy Prediction

Zhen Yang, Yanpeng Dong, Jiayu Wang, Heng Wang, Lichao Ma, Zijian Cui, Qi Liu, Haoran Pei, Kexin Zhang, Chao Zhang

机构 * Beijing Mechanical Equipment Institute（北京机械设备研究所） 纠错

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

Comments TCSVT Accepted version (not the final published version)

Journal ref IEEE Transactions on Circuits and Systems for Video Technology, 2025, Print ISSN: 1051-8215, Online ISSN: 1558-2205

CaR1: A Multi-Modal Baseline for BEV Vehicle Segmentation via Camera-Radar Fusion

Santiago Montiel-Marín, Angel Llamazares, Miguel Antunes-García, Fabio Sánchez-García, Luis M. Bergasa

机构 * Department of Electronics. University of Alcalá, Community of Madrid, Spain（电子系。阿尔卡拉大学，马德里社区） 纠错

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

Comments 4 pages, 2 figures

GaussianFusionOcc: A Seamless Sensor Fusion Approach for 3D Occupancy Prediction Using 3D Gaussians

Tomislav Pavković, Mohammad-Ali Nikouei Mahani, Johannes Niedermayer, Johannes Betz

机构 * Technical University of Munich（慕尼黑技术大学） ； BMW Group（宝马集团） ； Munich Institute of Robotics and Machine Intelligence（慕尼黑机器人与智能机械研究所） 纠错

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

Minimizing Occlusion Effect on Multi-View Camera Perception in BEV with Multi-Sensor Fusion

Sanjay Kumar, Hiep Truong, Sushil Sharma, Ganesh Sistu, Tony Scanlan, Eoin Grua, Ciarán Eising

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

Comments Accepted form publishing at the Electronic Imaging - Autonomous Vehicles and Machines Conference

Estimation of Closest In-Path Vehicle (CIPV) by Low-Channel LiDAR and Camera Sensor Fusion for Autonomous Vehicle

Hyunjin Bae, Gu Lee, Jaeseung Yang, Gwanjun Shin, Yongseob Lim, Gyeungho Choi

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

Comments 13 pages, 19 figures, submitted to MDPI Sensors

TFusionOcc: T-Primitive Based Object-Centric Multi-Sensor Fusion Framework for 3D Occupancy Prediction

TFusionOcc：基于T-原语的对象中心多传感器融合框架用于3D占用预测

Zhenxing Ming, Yaoqi Huang, Julie Stephany Berrio, Mao Shan, Stewart Worrall

机构 * Australian Centre for Robotics（澳大利亚机器人中心） 纠错

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

AI总结 本文提出TFusionOcc框架，通过T-原语实现3D语义占用预测，结合概率模型和多阶段融合架构，实验显示其在nuScenes数据集上表现优异。

LiDAR-BIND-T: Improved and Temporally Consistent Sensor Modality Translation and Fusion for Robotic Applications

Niels Balemans, Ali Anwar, Jan Steckel, Siegfried Mercelis

机构 * IDLab - Faculty of Applied Engineering, University of Antwerp - imec（IDLab - 应用工程学院，安特卫普大学 - imec） ； Cosys-Lab - Faculty of Applied Engineering, University of Antwerp（Cosys-Lab - 应用工程学院，安特卫普大学） ； Flanders Make Strategic Research Centre（弗拉芒制造战略研究中心） 纠错

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

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

Sensor Fusion by Spatial Encoding for Autonomous Driving

Quoc-Vinh Lai-Dang, Jihui Lee, Bumgeun Park, Dongsoo Har

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

Comments This paper has been accepted for Lecture presentation at the 2023 IEEE SENSORS conference

DIDLM: A SLAM Dataset for Difficult Scenarios Featuring Infrared, Depth Cameras, LIDAR, 4D Radar, and Others under Adverse Weather, Low Light Conditions, and Rough Roads

DIDLM：一种针对困难场景的SLAM数据集，包含红外、深度相机、LIDAR、4D雷达等，在恶劣天气、低光条件和粗糙路面下

Weisheng Gong, Chen He, Kaijie Su, Qingyong Li, Tong Wu, Z. Jane Wang

机构 * School of Information Science and Technology, Northwest University（信息科学与技术学院，西北大学） ； Department of Electrical and Computer Engineering, The University of British Columbia（电气与计算机工程系，不列颠哥伦比亚大学） 纠错

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

AI总结 本文提出DIDLM数据集，包含红外、深度相机、LIDAR、4D雷达等多传感器数据，用于解决恶劣天气、低光和粗糙路面下的SLAM问题，提供GPS/INS地面真实数据，支持自动驾驶和地面机器人应用。

GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Driving

Shuai Liu, Quanmin Liang, Zefeng Li, Boyang Li, Kai Huang

机构 * School of Computer Science and Engineering, Sun Yat-sen University（计算机科学与工程学院，中山大学） 纠错

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

Comments Accepted at NeurIPS2025 (Spotlight)

SpaRC-AD: A Baseline for Radar-Camera Fusion in End-to-End Autonomous Driving

Philipp Wolters, Johannes Gilg, Torben Teepe, Gerhard Rigoll

机构 * Technical University of Munich（慕尼黑技术大学） 纠错

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

Comments 8 pages, 4 figures, 5 tables

Driv3R: Learning Dense 4D Reconstruction for Autonomous Driving

Xin Fei, Wenzhao Zheng, Yueqi Duan, Wei Zhan, Masayoshi Tomizuka, Kurt Keutzer, Jiwen Lu

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

Comments Code is available at: https://github.com/Barrybarry-Smith/Driv3R

AlterMOMA: Fusion Redundancy Pruning for Camera-LiDAR Fusion Models with Alternative Modality Masking

Shiqi Sun, Yantao Lu, Ning Liu, Bo Jiang, JinChao Chen, Ying Zhang

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

Comments 17 pages, 3 figures, Accepted by NeurIPS 2024

OccFusion: Multi-Sensor Fusion Framework for 3D Semantic Occupancy Prediction

Zhenxing Ming, Julie Stephany Berrio, Mao Shan, Stewart Worrall

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

Improving Extrinsics between RADAR and LIDAR using Learning

Peng Jiang, Srikanth Saripalli

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

Comments accepted in IV 2023

MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving

Gopi Krishna Erabati, Helder Araujo

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

Comments Accepted at the ICPR 2022 Workshop DLVDR2022

CRUISE: Vision-Language Model-Guided Uncertainty-Aware Cross-Modal Sensor Fusion for Robust Autonomous Driving

CRUISE：面向鲁棒自动驾驶的视觉语言模型引导的不确定性感知跨模态传感器融合

Junyao Wang, Yulin Xu, Yu Li, Pramod Khargonekar, Mohammad Abdullah Al Faruque

机构 * University of California, Irvine（加利福尼亚大学欧文分校） 纠错

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

AI总结 针对现有不确定性感知融合方法泛化性差的问题，提出CRUISE框架，结合VLM引导的UQ模块与动态自适应机制，实现鲁棒的自动驾驶跨模态传感器融合。