自动驾驶

RLPR: Radar-to-LiDAR Place Recognition via Two-Stage Asymmetric Cross-Modal Alignment for Autonomous Driving

RLPR：面向自动驾驶的两阶段非对称跨模态对齐雷达-激光雷达地点识别

Zhangshuo Qi, Jingyi Xu, Luqi Cheng, Shichen Wen, Guangming Xiong

机构 * Beijing Institute of Technology（北京理工大学） ； Shanghai Jiaotong University（上海交通大学） 纠错

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

AI总结 提出RLPR框架，通过双流网络提取结构特征，并利用两阶段非对称跨模态对齐策略，实现雷达与激光雷达之间的鲁棒地点识别，在四个数据集上达到最优性能。

Comments Accepted by IEEE Robotics and Automation Letters (RA-L) 2026

LiSTAR: Ray-Centric World Models for 4D LiDAR Sequences in Autonomous Driving

LiSTAR: 基于4D激光雷达序列的射线中心世界模型用于自动驾驶

Pei Liu, Songtao Wang, Lang Zhang, Xingyue Peng, Yuandong Lyu, Jiaxin Deng, Songxin Lu, Weiliang Ma, Xueyang Zhang, Yifei Zhan, XianPeng Lang, Jun Ma

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

AI总结 LiSTAR通过射线中心变换器和混合柱形球形表示，实现高保真4D激光雷达数据生成，提升自动驾驶模拟的可控性和真实性。

DriveLiDAR4D: Sequential and Controllable LiDAR Scene Generation for Autonomous Driving

Kaiwen Cai, Xinze Liu, Xia Zhou, Hengtong Hu, Jie Xiang, Luyao Zhang, Xueyang Zhang, Kun Zhan, Yifei Zhan, Xianpeng Lang

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Comments AAAI2026

BEV-LIO(LC): BEV Image Assisted LiDAR-Inertial Odometry with Loop Closure

Haoxin Cai, Shenghai Yuan, Xinyi Li, Junfeng Guo, Jianqi Liu

机构 * School of Computer Science and Technology, Guangdong University of Technology（计算机科学与技术学院，广东技术大学） ； School of Electrical and Electronic Engineering, Nanyang Technological University（电子与电气工程学院，南洋理工大学） 纠错

专题命中 激光雷达 ：BEV(title,abstract)；LiDAR(title,abstract)；分类 cs.RO

HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Driving

R. D. Lin, Pengcheng Weng, Yinqiao Wang, Han Ding, Jinsong Han, Fei Wang

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Comments accepted by CVPR 2025

LiDAR-Based Place Recognition For Autonomous Driving: A Survey

Yongjun Zhang, Pengcheng Shi, Jiayuan Li

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.RO

Comments Accepted by ACM Computing Surveys

Journal ref ACM Computing Surveys 2024

PCB-RandNet: Rethinking Random Sampling for LIDAR Semantic Segmentation in Autonomous Driving Scene

XianFeng Han, Huixian Cheng, Hang Jiang, Dehong He, Guoqiang Xiao

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Comments Accepted by ICRA 2024. Code: https://github.com/huixiancheng/PCB-RandNet

Traversability Analysis for Autonomous Driving in Complex Environment: A LiDAR-based Terrain Modeling Approach

Hanzhang Xue, Hao Fu, Liang Xiao, Yiming Fan, Dawei Zhao, Bin Dai

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.RO

Comments accepted to Journal of Field Robotics

Journal ref Journal of Field Robotics, 2023, 1-25

Generalized Few-Shot 3D Object Detection of LiDAR Point Cloud for Autonomous Driving

Jiawei Liu, Xingping Dong, Sanyuan Zhao, Jianbing Shen

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

HALS: A Height-Aware Lidar Super-Resolution Framework for Autonomous Driving

George Eskandar, Sanjeev Sudarsan, Karim Guirguis, Janaranjani Palaniswamy, Bharath Somashekar, Bin Yang

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Lidar SLAM for Autonomous Driving Vehicles

Farhad Aghili

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.RO

CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving

Hui-Xian Cheng, Xian-Feng Han, Guo-Qiang Xiao

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Comments Accepted by ICME 2022

Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data

Corentin Sautier, Gilles Puy, Spyros Gidaris, Alexandre Boulch, Andrei Bursuc, Renaud Marlet

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Comments Accepted to CVPR2022

Predicting Vegetation Stratum Occupancy from Airborne LiDAR Data with Deep Learning

Ekaterina Kalinicheva, Loic Landrieu, Clément Mallet, Nesrine Chehata

专题命中 激光雷达 ：LiDAR(title,abstract)；occupancy(title,abstract)；分类 cs.CV

FPPN: Future Pseudo-LiDAR Frame Prediction for Autonomous Driving

Xudong Huang, Chunyu Lin, Haojie Liu, Lang Nie, Yao Zhao

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

How to Build a Curb Dataset with LiDAR Data for Autonomous Driving

Dongfeng Bai, Tongtong Cao, Jingming Guo, Bingbing Liu

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Comments 7 pages with 10 figures, submitted to 2022 IEEE International Conference on Robotics and Automation (ICRA)

Augmented LiDAR Simulator for Autonomous Driving

Jin Fang, Dingfu Zhou, Feilong Yan, Tongtong Zhao, Feihu Zhang, Yu Ma, Liang Wang, Ruigang Yang

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Comments 10 pages

Temporal LiDAR Frame Prediction for Autonomous Driving

David Deng, Avideh Zakhor

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Comments In 3DV 2020

Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

Ying Li, Lingfei Ma, Zilong Zhong, Fei Liu, Dongpu Cao, Jonathan Li, Michael A. Chapman

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Comments 21 pages, submitted to IEEE Transactions on Neural Networks and Learning Systems

Adversarial Objects Against LiDAR-Based Autonomous Driving Systems

Yulong Cao, Chaowei Xiao, Dawei Yang, Jing Fang, Ruigang Yang, Mingyan Liu, Bo Li

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

Autonomous Driving without a Burden: View from Outside with Elevated LiDAR

Nalin Jayaweera, Nandana Rajatheva, Matti Latva-aho

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.AI

An Optimal LiDAR Configuration Approach for Self-Driving Cars

Shenyu Mou, Yan Chang, Wenshuo Wang, Ding Zhao

专题命中 激光雷达 ：self-driving(title,abstract)；LiDAR(title,abstract)；分类 cs.RO

Comments Conference

A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving

Xiangyu Yue, Bichen Wu, Sanjit A. Seshia, Kurt Keutzer, Alberto L. Sangiovanni-Vincentelli

专题命中 激光雷达 ：autonomous driving(title,abstract)；LiDAR(title,abstract)；分类 cs.CV

3D Modeling and Automated Measurement of Concrete Cracks via Segment Anything Refinement and Visual Inertial LiDAR Fusion

通过段落任何精修和视觉惯性LiDAR融合进行混凝土裂缝的3D建模与自动测量

Pengru Deng, Jiapeng Yao, Chun Li, Su Wang, Xinrun Li, Varun Ojha, Xuhui He

机构 * School of Civil Engineering（土木工程学院） ； Central South University（中南大学） ； Hunan Provincial Key Laboratory for Disaster Prevention and Mitigation of Rail Transit Engineering Structures（湖南省铁路工程结构灾害预防与 mitigation 工程结构重点实验室） ； Nvidia ； School of Computing（计算学院） ； Newcastle University（新castle大学） 纠错

专题命中 激光雷达 ：LiDAR(title,title_cn)；分类 cs.RO、cs.CV

AI总结 本文提出了一种结合计算机视觉技术和多模态同时定位与建图（SLAM）的创新框架，用于二维裂缝检测、三维重建和三维自动裂缝测量，解决了现有方法在适应性和鲁棒性方面的不足，特别是在处理曲线或复杂几何形状时的挑战。

Comments Title and author list updated

Journal ref Computer-Aided Civil and Infrastructure Engineering, Volume 45, 2026, 100019, ISSN 1093-9687

CRISP: A Spatiotemporal Camera-Radar Backbone for Driving via Forecasting-Based World-Model Pretraining

CRISP：一种通过基于预测的世界模型预训练实现驾驶的时空相机-雷达主干网络

Jingyu Song, Yi Liu, Katherine A. Skinner

机构 * Department of Robotics, University of Michigan（密歇根大学机器人系） 纠错

专题命中 激光雷达 ：BEV(abstract,abstract_cn)；LiDAR(abstract,abstract_cn)；autonomous driving(abstract)；occupancy(abstract)

AI总结 研究通过基于预测的表示学习预训练时空相机-雷达主干网络CRISP，利用历史多视图图像和雷达扫描，通过预测未来激光雷达点云学习统一鸟瞰图表示，介绍相关组件，实验表明其能提升点云预测并有效迁移至下游任务。

Comments 17 pages, under review

Multi-Scale Neighborhood Occupancy Masked Autoencoder for Self-Supervised Learning in LiDAR Point Clouds

Mohamed Abdelsamad, Michael Ulrich, Claudius Gläser, Abhinav Valada

专题命中 激光雷达 ：occupancy(title,abstract)；LiDAR(title)；分类 cs.RO、cs.CV、cs.AI

Offline-Online Hierarchical 3D Global Relocalization With Synthetic LiDAR Sensing and Descriptor-Space Retrieval

离线-在线分层3D全局重定位与合成LiDAR感知及描述空间检索

Jiahua Ren, Kai Shen, Muhua Zhang, Lei Ma

机构 * School of Electrical Engineering, Southwest Jiaotong University（西南交通大学电气工程学院） 纠错

专题命中 激光雷达 ：LiDAR(title,title_cn)；分类 cs.RO

AI总结 本文提出一种离线-在线分层框架，通过分离搜索空间提升大规模空间中的重定位效率和精度，实测平均重定位时间3秒，精度8厘米，计算效率提升一个数量级。

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge

面向边缘设备点云分类的合成激光雷达数据生成与确定性下采样

Niclas Meyer, Stefan Reitmann

机构 * Chemnitz University of Technology（开姆尼茨工业大学） 纠错

专题命中 激光雷达 ：LiDAR(title,summary_cn)；分类 cs.RO

AI总结 本文针对三维深度学习框架在边缘设备部署的瓶颈，提出适配树莓派5的硬件受限工作流，通过合成LiDAR数据集和特征驱动的CPL层，实现边缘端50 FPS推理与88.36%分类准确率，验证了边缘实时三维感知的可行性。

Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps

利用点云密度地图高效关闭LiDAR基于SLAM中的环路

Saurabh Gupta, Tiziano Guadagnino, Benedikt Mersch, Niklas Trekel, Meher V. R. Malladi, Cyrill Stachniss

机构 * University of Bonn, Center for Robotics（波恩大学机器人中心） ； Lamarr Institute for Machine Learning and Artificial Intelligence（拉马尔机器学习与人工智能研究所） 纠错

专题命中 激光雷达 ：LiDAR(title,title_cn)；分类 cs.RO

AI总结 本文提出了一种鲁棒的环路关闭检测方法，通过生成局部地图并使用地面对齐模块处理平面和非平面运动，实现高效的SLAM系统。

Comments Accepted for publication at the International Journal of Robotics Research on 14 April, 2026

Neural LiDAR Bundle Adjustment

神经激光雷达光束平差

Chin Yung Anson Hon, Kaicheng Zhang, Sen Wang

机构 * Imperial College London（伦敦帝国理工学院） 纠错

专题命中 激光雷达 ：LiDAR(title,summary_cn)；分类 cs.RO

AI总结 研究探索RGB NeRFs和LiDAR NeRFs关键设计差异，发现体素采样密度对LiDAR NeRF重要，据此提出Neural LiDAR Bundle Adjustment算法，实验证明其在多视点云配准和3D映射中有出色性能。

Comments 8 pages, 8 figures, 4 tables