自动驾驶 - arXivDaily 专题

1905.08955 2019-05-23 cs.CV cs.AI 86%

Domain Adaptation for Vehicle Detection from Bird's Eye View LiDAR Point Cloud Data

Khaled Saleh, Ahmed Abobakr, Mohammed Attia, Julie Iskander, Darius Nahavandi, Mohammed Hossny

专题命中激光雷达：LiDAR(title,abstract)；self-driving(abstract)；BEV(abstract)；分类 cs.CV、cs.AI

Comments Under review for IEEE SMC 2019

2606.30147 2026-07-29 cs.CV 版本更新 85%

T2LDM++: A Self-Conditioned Representation Guided Diffusion Model for Realistic Text-to-LiDAR Scene Generation

T2LDM++：一种用于真实文本到激光雷达场景生成的自条件表示引导扩散模型

Wentao Qu, Qi Zhang, Chenxu Wang, Guofeng Mei, Yongfei Liu, Xiaoshui Huang, Gim Hee Lee, Liang Xiao

机构 * School of Computer Science and Engineering（计算机科学与工程学院）； Nanjing University of Science and Technology（南京理工大学）； Faculty of Data Science（数据科学学院）； City University of Macau（澳门城市大学）； Beijing Institute of Technology（北京理工大学）； Fondazione Bruno Kessler（布鲁诺·凯瑟尔基金会）； School of Public Health（公共卫生学院）； Shanghai Jiao Tong University（上海交通大学）； School of Computing（计算机学院）； National University of Singapore（新加坡国立大学）

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

AI总结针对文本-激光雷达数据稀缺导致场景过平滑和可控性不足的问题，提出T2LDM++模型，通过自条件表示引导（SCRG）提供重建监督，并构建高质量基准数据集，实现几何细节丰富的激光雷达场景生成。

2607.12419 2026-07-15 cs.CV 新提交 85%

DeGuNet: Depth-Guided Ultra-Compact Backbones for Efficient LiDAR-Camera 3D Detection

DeGuNet：用于高效激光雷达-相机3D检测的深度引导超紧凑骨干网络

Haifa Zhang, Yijing Wang, Peixi Peng, Zhiqiang Zuo

机构 * Tianjin University（天津大学）； Peking University（北京大学）

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

AI总结研究针对自动驾驶中激光雷达与相机融合检测依赖2D预训练骨干网络的问题，提出DeGuNet，通过稀疏感知机制有效对齐图像与激光雷达深度，实验证明其能消除架构冗余，提升效率并提高mAP，建立参数高效多模态3D感知新范式。

Comments Accepted to ECCV 2026

2603.19830 2026-04-21 cs.RO 85%

Real-Time Structural Detection for Indoor Navigation from 3D LiDAR Using Bird's-Eye-View Images

基于3D激光雷达的实时室内导航鸟瞰图像结构检测

Guanliang Li, Pedro Espinosa-Angulo, David Perez-Saura, Santiago Tapia-Fernandez

机构 * Universidad Politécnica de Madrid（马德里理工大学）

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

AI总结本文提出一种轻量实时框架，通过将3D激光雷达数据投影到2D鸟瞰图像中，实现高效结构检测，采用几何方法和YOLO-OBB深度学习检测器，结合时空融合模块提升稳定性，实验证明YOLO-OBB在资源受限平台上的高效鲁棒性。

2604.12331 2026-04-15 cs.CV 85%

HyperLiDAR: Adaptive Post-Deployment LiDAR Segmentation via Hyperdimensional Computing

HyperLiDAR: 一种基于超维度计算的自适应部署后激光雷达分割方法

Ivannia Gomez Moreno, Yi Yao, Ye Tian, Xiaofan Yu, Flavio Ponzina, Michael Sullivan, Jingyi Zhang, Mingyu Yang, Hun Seok Kim, Tajana Rosing

机构 * UCSD（加州大学圣迭戈分校）； UC Merced（加州大学默塞德分校）； SDSU（南达科他州立大学）； UMich（密歇根大学）

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

AI总结本文提出HyperLiDAR，一种基于超维度计算的轻量级激光雷达分割框架，解决部署后适应性问题，通过缓冲区选择策略提升效率，实现实时适应与高效率重训练。

2604.00371 2026-04-02 cs.CV 85%

Neural Reconstruction of LiDAR Point Clouds under Jamming Attacks via Full-Waveform Representation and Simultaneous Laser Sensing

通过全波形表示和同时激光感知实现对抗攻击下的LiDAR点云神经重建

Ryo Yoshida, Takami Sato, Wenlun Zhang, Yuki Hayakawa, Shota Nagai, Takahiro Kado, Taro Beppu, Ibuki Fujioka, Yunshan Zhong, Kentaro Yoshioka

机构 * Keio University（庆应义塾大学）； Sony Semiconductor Solutions（索尼半导体解决方案公司）； Hainan University（海南大学）

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

AI总结本文提出PULSAR-Net，利用全波形表示和同时激光感知，在对抗攻击下重建真实点云，通过轴向空间注意力机制识别攻击信号，实验显示其在静态和驾驶场景中对车辆的重建率分别达92%和73%。

2503.10149 2025-03-14 cs.CV 85%

Unlocking Generalization Power in LiDAR Point Cloud Registration

Zhenxuan Zeng, Qiao Wu, Xiyu Zhang, Lin Yuanbo Wu, Pei An, Jiaqi Yang, Ji Wang, Peng Wang

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

Comments Accepted by CVPR 2025

2412.01407 2024-12-04 cs.CV 85%

HoloDrive: Holistic 2D-3D Multi-Modal Street Scene Generation for Autonomous Driving

Zehuan Wu, Jingcheng Ni, Xiaodong Wang, Yuxin Guo, Rui Chen, Lewei Lu, Jifeng Dai, Yuwen Xiong

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

2404.17298 2024-11-05 cs.RO 85%

Automatic Target-Less Camera-LiDAR Calibration From Motion and Deep Point Correspondences

Kürsat Petek, Niclas Vödisch, Johannes Meyer, Daniele Cattaneo, Abhinav Valada, Wolfram Burgard

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

Journal ref IEEE Robotics and Automation Letters, vol. 9, no. 11, pp. 9978-9985, November 2024

2409.06827 2024-09-12 cs.CV 85%

Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point Clouds

Mu Cai, Chenxu Luo, Yong Jae Lee, Xiaodong Yang

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

Comments IROS 2024

2405.05131 2024-05-09 cs.RO 85%

DenserRadar: A 4D millimeter-wave radar point cloud detector based on dense LiDAR point clouds

Zeyu Han, Junkai Jiang, Xiaokang Ding, Qingwen Meng, Shaobing Xu, Lei He, Jianqiang Wang

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

2304.14811 2024-01-23 cs.CV 85%

NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields

Junge Zhang, Feihu Zhang, Shaochen Kuang, Li Zhang

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

2311.04501 2023-11-09 cs.CV 85%

PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds

Hao Yang, Haiyang Wang, Di Dai, Liwei Wang

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

2304.12589 2023-04-26 cs.CV 85%

ContrastMotion: Self-supervised Scene Motion Learning for Large-Scale LiDAR Point Clouds

Xiangze Jia, Hui Zhou, Xinge Zhu, Yandong Guo, Ji Zhang, Yuexin Ma

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

2212.04265 2022-12-09 eess.IV 85%

DONEX: Real-time occupancy grid based dynamic echo classification for 3D point cloud

Niklas Stralau, Chengxuan Fu

专题命中激光雷达：occupancy(title,abstract)；autonomous driving(abstract)；LiDAR(abstract)；分类 eess.IV

Comments Published on "Fifth IEEE International Conference on Image Processing, Applications and Systems (IPAS 2022)", 5-7 December 2022, Genova, Italy

2104.09035 2022-07-26 cs.CV 85%

Lidar Point Cloud Guided Monocular 3D Object Detection

Liang Peng, Fei Liu, Zhengxu Yu, Senbo Yan, Dan Deng, Zheng Yang, Haifeng Liu, Deng Cai

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

Comments ECCV 2022

2109.11453 2021-09-24 cs.CV 85%

Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds

Xuemeng Yang, Hao Zou, Xin Kong, Tianxin Huang, Yong Liu, Wanlong Li, Feng Wen, Hongbo Zhang

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

Comments 8 pages, 4 figures, accepted by The 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems

2007.08854 2020-09-23 cs.CV cs.AI cs.RO eess.IV 85%

DVI: Depth Guided Video Inpainting for Autonomous Driving

Miao Liao, Feixiang Lu, Dingfu Zhou, Sibo Zhang, Wei Li, Ruigang Yang

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

2005.13102 2020-05-28 cs.CV stat.ML 85%

Road Segmentation on low resolution Lidar point clouds for autonomous vehicles

Leonardo Gigli, B Ravi Kiran, Thomas Paul, Andres Serna, Nagarjuna Vemuri, Beatriz Marcotegui, Santiago Velasco-Forero

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

Comments ISPRS 2020

2004.03048 2020-04-08 cs.CV 85%

Depth Sensing Beyond LiDAR Range

Kai Zhang, Jiaxin Xie, Noah Snavely, Qifeng Chen

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

Comments Accepted to CVPR 2020

2602.13267 2026-05-13 cs.CV cs.RO eess.IV 85%

SOAR: Regression-based LiDAR Relocalization for UAVs

SOAR：基于回归的无人机激光雷达重定位

Hengyu Mu, Jianshi Wu, Yuxin Guo, XianLian Lin, Qingyong Hu, Sheng Ao, Chenglu Wen, Cheng Wang

机构 * Fujian Key Laboratory of Sensing and Computing for Smart Cities, Xiamen University（厦门大学智慧城市感知与计算重点实验室）； Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University（中国教育部多媒体可信感知与高效计算重点实验室）； Department of Computer Science at the University of Oxford（牛津大学计算机科学系）

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

AI总结本文提出SOAR框架，通过局部滑动窗口注意力模块和坐标无关特征初始化模块，提升无人机在GNSS拒止环境下的激光雷达重定位精度，实验表明其在UAVLoc上提升了40%的成功率并降低了10米以上的均误差。

Comments 24 pages, 14 figures

2409.18092 2025-08-05 cs.CV cs.AI cs.RO 85%

DiffSSC: Semantic LiDAR Scan Completion using Denoising Diffusion Probabilistic Models

Helin Cao, Sven Behnke

机构 * Autonomous Intelligent Systems group, Computer Science Institute VI – Intelligent Systems and Robotics – and the Center for Robotics and the Lamarr Institute for Machine Learning and Artificial Intelligence, University of Bonn, Germany（自主智能系统组，计算机科学研究所VI——智能系统与机器人——和机器人中心以及拉马尔人工智能与机器学习研究所，波恩大学，德国）

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

Comments 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025), Hangzhou, China, Oct 2025

2412.00592 2025-05-27 cs.CV cs.AI cs.LG cs.RO 85%

LiDAR-EDIT: LiDAR Data Generation by Editing the Object Layouts in Real-World Scenes

Shing-Hei Ho, Bao Thach, Minghan Zhu

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

Comments Accepted to IEEE International Conference on Robotics and Automation (ICRA). 6 pages, 7 figures

2411.00600 2024-11-04 cs.CV cs.AI cs.RO 85%

On Deep Learning for Geometric and Semantic Scene Understanding Using On-Vehicle 3D LiDAR

Li Li

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

Comments PhD thesis (Durham University, Computer Science), 149 pages (the 2024 BMVA Sullivan Doctoral Thesis Prize runner-up). Includes published content from arXiv:2407.10159 (ECCV 2024 ORAL), arXiv:2303.11203 (CVPR 2023), and arXiv:2406.10068 (3DV 2021), with minor revisions to the examined version: https://etheses.dur.ac.uk/15738/

2012.09242 2023-11-20 cs.CV cs.AI cs.LG cs.RO 85%

S3CNet: A Sparse Semantic Scene Completion Network for LiDAR Point Clouds

Ran Cheng, Christopher Agia, Yuan Ren, Xinhai Li, Liu Bingbing

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

Comments 14 pages

Journal ref PMLR 155 (2021) 2148-2161

2102.12010 2021-07-06 cs.RO cs.AI cs.CV 85%

PixSet : An Opportunity for 3D Computer Vision to Go Beyond Point Clouds With a Full-Waveform LiDAR Dataset

Jean-Luc Déziel, Pierre Merriaux, Francis Tremblay, Dave Lessard, Dominique Plourde, Julien Stanguennec, Pierre Goulet, Pierre Olivier

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

Comments 7 pages, 9 figures

2009.01875 2020-09-07 cs.CV cs.RO eess.IV 85%

Depth Completion via Inductive Fusion of Planar LIDAR and Monocular Camera

Chen Fu, Chiyu Dong, Christoph Mertz, John M. Dolan

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

Comments Accepted at IROS 2020

1910.04871 2020-03-11 cs.CV cs.LG cs.RO eess.IV 85%

Global visual localization in LiDAR-maps through shared 2D-3D embedding space

Daniele Cattaneo, Matteo Vaghi, Simone Fontana, Augusto Luis Ballardini, Domenico Giorgio Sorrenti

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

Comments Accepted for presentation at IEEE ICRA 2020

1910.11147 2019-10-25 cs.CV cs.RO eess.IV 85%

DCT Maps: Compact Differentiable Lidar Maps Based on the Cosine Transform

Alexander Schaefer, Lukas Luft, Wolfram Burgard

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

Comments 8 pages

Journal ref IEEE Robotics and Automation Letters (Volume: 3, Issue: 2, April 2018)

2109.08224 2021-09-20 cs.CV cs.RO 84%

A Divide-and-Merge Point Cloud Clustering Algorithm for LiDAR Panoptic Segmentation

Yiming Zhao, Xiao Zhang, Xinming Huang

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

Comments Submitted to ICRA'22, code link: https://github.com/placeforyiming/Divide-and-Merge-LiDAR-Panoptic-Cluster

1. 激光雷达 3131 篇

Domain Adaptation for Vehicle Detection from Bird's Eye View LiDAR Point Cloud Data

T2LDM++: A Self-Conditioned Representation Guided Diffusion Model for Realistic Text-to-LiDAR Scene Generation

DeGuNet: Depth-Guided Ultra-Compact Backbones for Efficient LiDAR-Camera 3D Detection

Real-Time Structural Detection for Indoor Navigation from 3D LiDAR Using Bird's-Eye-View Images

HyperLiDAR: Adaptive Post-Deployment LiDAR Segmentation via Hyperdimensional Computing

Neural Reconstruction of LiDAR Point Clouds under Jamming Attacks via Full-Waveform Representation and Simultaneous Laser Sensing

Unlocking Generalization Power in LiDAR Point Cloud Registration

HoloDrive: Holistic 2D-3D Multi-Modal Street Scene Generation for Autonomous Driving

Automatic Target-Less Camera-LiDAR Calibration From Motion and Deep Point Correspondences

Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point Clouds

DenserRadar: A 4D millimeter-wave radar point cloud detector based on dense LiDAR point clouds

NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields

PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds

ContrastMotion: Self-supervised Scene Motion Learning for Large-Scale LiDAR Point Clouds

DONEX: Real-time occupancy grid based dynamic echo classification for 3D point cloud

Lidar Point Cloud Guided Monocular 3D Object Detection

Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds

DVI: Depth Guided Video Inpainting for Autonomous Driving

Road Segmentation on low resolution Lidar point clouds for autonomous vehicles

Depth Sensing Beyond LiDAR Range

SOAR: Regression-based LiDAR Relocalization for UAVs

DiffSSC: Semantic LiDAR Scan Completion using Denoising Diffusion Probabilistic Models

LiDAR-EDIT: LiDAR Data Generation by Editing the Object Layouts in Real-World Scenes

On Deep Learning for Geometric and Semantic Scene Understanding Using On-Vehicle 3D LiDAR

S3CNet: A Sparse Semantic Scene Completion Network for LiDAR Point Clouds

PixSet : An Opportunity for 3D Computer Vision to Go Beyond Point Clouds With a Full-Waveform LiDAR Dataset

Depth Completion via Inductive Fusion of Planar LIDAR and Monocular Camera

Global visual localization in LiDAR-maps through shared 2D-3D embedding space

DCT Maps: Compact Differentiable Lidar Maps Based on the Cosine Transform

A Divide-and-Merge Point Cloud Clustering Algorithm for LiDAR Panoptic Segmentation