自动驾驶 - arXivDaily 专题

2306.16551 2023-06-30 cs.CV cs.RO eess.IV 82%

Analysis of LiDAR Configurations on Off-road Semantic Segmentation Performance

Jinhee Yu, Jingdao Chen, Lalitha Dabbiru, Christopher T. Goodin

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

2302.06414 2023-02-14 cs.RO cs.AI cs.CV 82%

LAPTNet-FPN: Multi-scale LiDAR-aided Projective Transform Network for Real Time Semantic Grid Prediction

Manuel Alejandro Diaz-Zapata, David Sierra González, Özgür Erkent, Jilles Dibangoye, Christian Laugier

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

Comments 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE Robotics and Automation Society, May 2023, London, United Kingdom

2211.14445 2022-11-29 cs.CV cs.AI cs.RO 82%

LAPTNet: LiDAR-Aided Perspective Transform Network

Manuel Alejandro Diaz-Zapata, Özgür Erkent, Christian Laugier, Jilles Dibangoye, David Sierra González

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

Comments ICARCV 2022 - 17th International Conference on Control, Automation, Robotics and Vision, Dec 2022, Singapore, Singapore

2109.03569 2022-11-28 cs.CV cs.AI cs.RO 82%

LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR

Florent Bartoccioni, Éloi Zablocki, Patrick Pérez, Matthieu Cord, Karteek Alahari

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

2210.09482 2022-10-31 cs.CR 82%

You Can't See Me: Physical Removal Attacks on LiDAR-based Autonomous Vehicles Driving Frameworks

Yulong Cao, S. Hrushikesh Bhupathiraju, Pirouz Naghavi, Takeshi Sugawara, Z. Morley Mao, Sara Rampazzi

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

Comments Accepted to the 32nd USENIX Security Symposium (2023)

2210.11750 2022-10-24 cs.CV cs.RO eess.IV 82%

Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data

Kazuto Nakashima, Yumi Iwashita, Ryo Kurazume

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

Comments Accepted to WACV 2023

2203.01816 2022-09-07 cs.RO cs.CV eess.IV 82%

Intensity Image-based LiDAR Fiducial Marker System

Yibo Liu, Hunter Schofield, Jinjun Shan

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

Comments 8 pages

2203.05698 2022-08-02 cs.RO cs.AI cs.CV cs.LG 82%

Learning-based Localizability Estimation for Robust LiDAR Localization

Julian Nubert, Etienne Walther, Shehryar Khattak, Marco Hutter

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

Comments 8 pages, 7 figures, 4 tables

2109.08263 2021-11-18 eess.IV cs.CV cs.RO 82%

Neural Network Based Lidar Gesture Recognition for Realtime Robot Teleoperation

Simon Chamorro, Jack Collier, François Grondin

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

Journal ref 2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)

2111.01246 2021-11-03 eess.SP 82%

Beyond Point Clouds: A Knowledge-Aided High Resolution Imaging Radar Deep Detector for Autonomous Driving

Ruxin Zheng, Shunqiao Sun, David Scharff, Teresa Wu

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

Comments 6 pages, 9 figures

2102.11952 2021-08-03 cs.CV cs.RO eess.IV 82%

Learning to Drop Points for LiDAR Scan Synthesis

Kazuto Nakashima, Ryo Kurazume

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

Comments Accepted to IROS 2021

2106.11516 2021-07-02 cs.RO cs.AI cs.CV 82%

SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure

Lin Li, Xin Kong, Xiangrui Zhao, Wanlong Li, Feng Wen, Hongbo Zhang, Yong Liu

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

Comments 8 pages. Accepted by ICRA-2021

2105.12774 2021-05-28 cs.CV cs.AI cs.LG cs.RO 82%

DSLR: Dynamic to Static LiDAR Scan Reconstruction Using Adversarially Trained Autoencoder

Prashant Kumar, Sabyasachi Sahoo, Vanshil Shah, Vineetha Kondameedi, Abhinav Jain, Akshaj Verma, Chiranjib Bhattacharyya, Vinay Viswanathan

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

Comments 17 pages, 15 figures, Accepted at AAAI 2021

2103.15967 2021-03-31 cs.RO cs.CV eess.IV 82%

Detecting and Mapping Trees in Unstructured Environments with a Stereo Camera and Pseudo-Lidar

Brian H. Wang, Carlos Diaz-Ruiz, Jacopo Banfi, Mark Campbell

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

Comments Accepted to the 2021 IEEE International Conference on Robotics and Automation (ICRA)

2012.05740 2020-12-11 cs.CV cs.AI cs.RO 82%

R-AGNO-RPN: A LIDAR-Camera Region Deep Network for Resolution-Agnostic Detection

Ruddy Théodose, Dieumet Denis, Thierry Chateau, Vincent Frémont, Paul Checchin

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

2003.04260 2020-03-26 cs.CV cs.RO eess.IV 82%

SOIC: Semantic Online Initialization and Calibration for LiDAR and Camera

Weimin Wang, Shohei Nobuhara, Ryosuke Nakamura, Ken Sakurada

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

2003.01979 2020-03-05 cs.IT eess.SP math.IT 82%

Factory Automation: Resource Allocation of an Elevated LiDAR System with URLLC Requirements

Nalin Jayaweera, Dileepa Marasinghe, Nandana Rajatheva, Matti Latva-aho

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

Comments Accepted in 6G Wireless Summit 2020

1908.07488 2020-01-14 eess.SP 82%

LIDAR Data for Deep Learning-Based mmWave Beam-Selection

Aldebaro Klautau, Nuria González-Prelcic, Robert W. Heath

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

Comments 10 pages, IEEE; update: fixed typo

1909.06700 2019-09-17 cs.RO cs.CV eess.IV 82%

Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV

Jiarong Lin, Fu Zhang

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

1907.07160 2019-07-17 cs.CV cs.RO eess.IV 82%

EnforceNet: Monocular Camera Localization in Large Scale Indoor Sparse LiDAR Point Cloud

Yu Chen, Guan Wang

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

1807.00275 2018-07-04 cs.CV cs.AI cs.LG cs.RO 82%

Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera

Fangchang Ma, Guilherme Venturelli Cavalheiro, Sertac Karaman

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

Comments Software: https://github.com/fangchangma/self-supervised-depth-completion . Video: https://youtu.be/bGXfvF261pc . 12 pages, 6 figures, 3 tables

2602.10492 2026-02-12 cs.CV cs.RO 82%

End-to-End LiDAR optimization for 3D point cloud registration

端到端激光雷达优化用于3D点云配准

Siddhant Katyan, Marc-André Gardner, Jean-François Lalonde

机构 * Université Laval（拉瓦尔大学）； Bentley Systems（贝恩特系统）

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

AI总结本文提出端到端自适应激光雷达框架，通过动态调整参数优化点云配准，提升精度与效率，并在CARLA模拟中验证其优于固定参数方法的性能。

Comments 36th British Machine Vision Conference 2025, {BMVC} 2025, Sheffield, UK, November 24-27, 2025. Project page: https://lvsn.github.io/e2e-lidar-registration/

2412.15199 2024-12-20 cs.CV cs.LG cs.RO 82%

LiDAR-RT: Gaussian-based Ray Tracing for Dynamic LiDAR Re-simulation

Chenxu Zhou, Lvchang Fu, Sida Peng, Yunzhi Yan, Zhanhua Zhang, Yong Chen, Jiazhi Xia, Xiaowei Zhou

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

Comments Project page: https://zju3dv.github.io/lidar-rt

2302.07025 2023-11-09 cs.CV cs.LG eess.IV 82%

Optimal Transport for Change Detection on LiDAR Point Clouds

Marco Fiorucci, Peter Naylor, Makoto Yamada

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

Comments This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No101027956. Marie Skłodowska-Curie Action (Individual Fellowship): OPtimal Transport for Identifying Marauder Activities on LiDAR (OPTIMAL) https://cordis.europa.eu/project/id/101027956

Journal ref IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 982-985

2301.09257 2023-06-21 cs.CV cs.RO 82%

Real-Time Simultaneous Localization and Mapping with LiDAR intensity

Wenqiang Du, Giovanni Beltrame

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

Comments Accepted by ICRA 2023, code released: https://github.com/SnowCarter/Intensity_based_LiDAR_SLAM.git

2210.14612 2023-05-16 cs.CV cs.LG cs.NE cs.RO 82%

Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception

Marc Uecker, Tobias Fleck, Marcel Pflugfelder, J. Marius Zöllner

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

Comments Accepted at the NeurIPS 2022 Workshop on Machine Learning for Autonomous Driving (ML4AD). Changed in v3: corrected erroneously cited mIoU score for PolarNet

2007.13834 2021-11-10 cs.CV cs.LG eess.IV 82%

Adaptive LiDAR Sampling and Depth Completion using Ensemble Variance

Eyal Gofer, Shachar Praisler, Guy Gilboa

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

Comments Accepted for publication in IEEE Transactions on Image Processing. For associated examples, see https://www.vision-and-sensing.com/post/adaptive-lidar-sampling-and-depth-completion-using-ensemble-variance-new-publication

2102.04960 2021-06-21 cs.CV cs.RO 82%

Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning

Huan Yin, Xuecheng Xu, Yue Wang, Rong Xiong

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

Comments Published by Frontiers in Robotics and AI. The published version is available at https://www.frontiersin.org/articles/10.3389/frobt.2021.661199/full . The source code is available at https://github.com/ZJUYH/radar-to-lidar-place-recognition

2105.01793 2021-05-06 cs.CV eess.IV 82%

Intensity Harmonization for Airborne LiDAR

David Jones, Nathan Jacobs

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

Comments IGARSS 2021. Project website with video and code at https://davidthomasjones.me/publications/airborne-lidar-intensity-harmonization

1911.10575 2019-12-03 eess.IV cs.CV cs.LG 82%

Unsupervised Neural Sensor Models for Synthetic LiDAR Data Augmentation

Ahmad El Sallab, Ibrahim Sobh, Mohamed Zahran, Mohamed Shawky

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

Comments Accepted in Machine learning for Autonomous Driving NeurIPS 2019 Workshop

1. 激光雷达 3148 篇

Analysis of LiDAR Configurations on Off-road Semantic Segmentation Performance

LAPTNet-FPN: Multi-scale LiDAR-aided Projective Transform Network for Real Time Semantic Grid Prediction

LAPTNet: LiDAR-Aided Perspective Transform Network

LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR

You Can't See Me: Physical Removal Attacks on LiDAR-based Autonomous Vehicles Driving Frameworks

Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data

Intensity Image-based LiDAR Fiducial Marker System

Learning-based Localizability Estimation for Robust LiDAR Localization

Neural Network Based Lidar Gesture Recognition for Realtime Robot Teleoperation

Beyond Point Clouds: A Knowledge-Aided High Resolution Imaging Radar Deep Detector for Autonomous Driving

Learning to Drop Points for LiDAR Scan Synthesis

SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure

DSLR: Dynamic to Static LiDAR Scan Reconstruction Using Adversarially Trained Autoencoder

Detecting and Mapping Trees in Unstructured Environments with a Stereo Camera and Pseudo-Lidar

R-AGNO-RPN: A LIDAR-Camera Region Deep Network for Resolution-Agnostic Detection

SOIC: Semantic Online Initialization and Calibration for LiDAR and Camera

Factory Automation: Resource Allocation of an Elevated LiDAR System with URLLC Requirements

LIDAR Data for Deep Learning-Based mmWave Beam-Selection

Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV

EnforceNet: Monocular Camera Localization in Large Scale Indoor Sparse LiDAR Point Cloud

Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera

End-to-End LiDAR optimization for 3D point cloud registration

LiDAR-RT: Gaussian-based Ray Tracing for Dynamic LiDAR Re-simulation

Optimal Transport for Change Detection on LiDAR Point Clouds

Real-Time Simultaneous Localization and Mapping with LiDAR intensity

Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception

Adaptive LiDAR Sampling and Depth Completion using Ensemble Variance

Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning

Intensity Harmonization for Airborne LiDAR

Unsupervised Neural Sensor Models for Synthetic LiDAR Data Augmentation