自动驾驶 - arXivDaily 专题

1902.09184 2019-02-27 cs.CV 79%

Towards Corner Case Detection for Autonomous Driving

Jan-Aike Bolte, Andreas Bär, Daniel Lipinski, Tim Fingscheidt

专题命中感知：autonomous driving(title,abstract)；分类 cs.CV

1807.02062 2018-11-30 cs.CV 79%

Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving

Peiliang Li, Tong Qin, Shaojie Shen

专题命中感知：autonomous driving(title,abstract)；分类 cs.CV

Comments 14 pages, 9 figures, eccv2018

1810.12536 2018-10-31 cs.RO 79%

Forest Tree Detection and Segmentation using High Resolution Airborne LiDAR

Lloyd Windrim, Mitch Bryson

专题命中感知：LiDAR(title,abstract)；分类 cs.RO

Comments Submitted to the IEEE International Conference on Robotics and Automation 2019

1809.05879 2018-09-18 cs.LG cs.CV stat.ML 79%

An FPGA-Accelerated Design for Deep Learning Pedestrian Detection in Self-Driving Vehicles

Abdallah Moussawi, Kamal Haddad, Anthony Chahine

专题命中感知：self-driving(title,abstract)；分类 cs.CV

Comments 7 pages. American University of Beirut, Faculty of Engineering and Architecture Student and Alumni Conference 2017 FEASAC

1808.08413 2018-08-28 eess.IV 79%

A Brief Survey and an Application of Semantic Image Segmentation for Autonomous Driving

Çağrı Kaymak, Ayşegül Uçar

专题命中感知：autonomous driving(title,abstract)；分类 eess.IV

Comments A chapter for Springer Book: Handbook of Deep Learning Applications, 2018,[ Pijush Samui, Editor]. (be published)

1801.04137 2018-08-01 cs.RO 79%

Multisensor Online Transfer Learning for 3D LiDAR-based Human Detection with a Mobile Robot

Zhi Yan, Li Sun, Tom Duckett, Nicola Bellotto

专题命中感知：LiDAR(title,abstract)；分类 cs.RO

Comments IROS'18 final version

1807.11546 2018-08-01 cs.CV 79%

Textual Explanations for Self-Driving Vehicles

Jinkyu Kim, Anna Rohrbach, Trevor Darrell, John Canny, Zeynep Akata

专题命中感知：self-driving(title,abstract)；分类 cs.CV

Comments Accepted to ECCV 2018

Journal ref European Conference on Computer Vision (ECCV), 2018

1807.01726 2018-07-06 cs.CV 79%

LaneNet: Real-Time Lane Detection Networks for Autonomous Driving

Ze Wang, Weiqiang Ren, Qiang Qiu

专题命中感知：autonomous driving(title,abstract)；分类 cs.CV

1805.08986 2018-05-24 cs.RO 79%

Deep Object Tracking on Dynamic Occupancy Grid Maps Using RNNs

Nico Engel, Stefan Hoermann, Philipp Henzler, Klaus Dietmayer

专题命中感知：occupancy(title,abstract)；分类 cs.RO

1805.01195 2018-05-04 cs.CV 79%

BirdNet: a 3D Object Detection Framework from LiDAR information

Jorge Beltran, Carlos Guindel, Francisco Miguel Moreno, Daniel Cruzado, Fernando Garcia, Arturo de la Escalera

专题命中感知：LiDAR(title,abstract)；分类 cs.CV

Comments Submittied to IEEE International Conference on Intelligent Transportation Systems 2018 (ITSC)

1804.01945 2018-04-06 cs.RO 79%

Synchronous Adversarial Feature Learning for LiDAR based Loop Closure Detection

Peng Yin, Yuqing He, Lingyun Xu, Yan Peng, Jianda Han, Weiliang Xu

专题命中感知：LiDAR(title,abstract)；分类 cs.RO

Comments 6 Pages, accepted by ACC2018

1711.07659 2017-11-22 cs.RO 79%

Towards Stable Adversarial Feature Learning for LiDAR based Loop Closure Detection

Lingyun Xu, Peng Yin, Haibo Luo, Yunhui Liu, Jianda Han

专题命中感知：LiDAR(title,abstract)；分类 cs.RO

Comments 8 pages, 14 figures, submitted to ICRA 2018

1711.02757 2017-11-09 cs.RO 79%

Real-Time Road Segmentation Using LiDAR Data Processing on an FPGA

Yecheng Lyu, Lin Bai, Xinming Huang

专题命中感知：LiDAR(title,abstract)；分类 cs.RO

Comments Under review at ISCAS 2018

1711.02079 2017-11-07 cs.RO 79%

Cone Detection using a Combination of LiDAR and Vision-based Machine Learning

Nico Messikommer, Simon Schaefer, Renaud Dubé, Mark Pfeiffer

专题命中感知：LiDAR(title,abstract)；分类 cs.RO

1709.07641 2017-09-25 cs.RO 79%

Characterization of a RS-LiDAR for 3D Perception

Zhe Wang, Yang Liu, Qinghai Liao, Haoyang Ye, Ming Liu, Lujia Wang

专题命中感知：LiDAR(title,abstract)；分类 cs.RO

Comments For ICRA2018

1708.09839 2017-09-01 cs.CV 79%

3D Visual Perception for Self-Driving Cars using a Multi-Camera System: Calibration, Mapping, Localization, and Obstacle Detection

Christian Häne, Lionel Heng, Gim Hee Lee, Friedrich Fraundorfer, Paul Furgale, Torsten Sattler, Marc Pollefeys

专题命中感知：self-driving(title,abstract)；分类 cs.CV

1703.10631 2017-04-03 cs.CV cs.LG 79%

Interpretable Learning for Self-Driving Cars by Visualizing Causal Attention

Jinkyu Kim, John Canny

专题命中感知：self-driving(title,abstract)；分类 cs.CV

1703.03613 2017-03-30 cs.CV 79%

Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks

Luca Caltagirone, Samuel Scheidegger, Lennart Svensson, Mattias Wahde

专题命中感知：LiDAR(title,abstract)；分类 cs.CV

1701.00198 2017-01-03 cs.CV cs.CE cs.CG 79%

A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data

Hamid Hamraz, Marco A. Contreras, Jun Zhang

专题命中感知：LiDAR(title,abstract)；分类 cs.CV

Journal ref International Journal of Applied Earth Observation and Geoinformation 52 (pp. 532-541): Elsevier (2016)

1607.06708 2016-11-17 cs.RO 79%

A Statistical Method for Parking Spaces Occupancy Detection via Automotive Radars

Qi Luo, Romesh Saigal, Robert Hampshire, Xinyi Wu

专题命中感知：occupancy(title,abstract)；分类 cs.RO

Comments 5 pages

1609.00361 2016-09-13 cs.CV 79%

Autonomous driving challenge: To Infer the property of a dynamic object based on its motion pattern using recurrent neural network

Mona Fathollahi, Rangachar Kasturi

专题命中感知：autonomous driving(title,abstract)；分类 cs.CV

1607.00971 2016-07-05 cs.CV 79%

Can we unify monocular detectors for autonomous driving by using the pixel-wise semantic segmentation of CNNs?

Eduardo Romera, Luis M. Bergasa, Roberto Arroyo

专题命中感知：autonomous driving(title,abstract)；分类 cs.CV

Comments Extended abstract presented in IV16-WS Deepdriving (http://iv2016.berkeleyvision.org/)

1512.06735 2016-04-28 cs.CV 79%

Instance-Level Segmentation for Autonomous Driving with Deep Densely Connected MRFs

Ziyu Zhang, Sanja Fidler, Raquel Urtasun

专题命中感知：autonomous driving(title,abstract)；分类 cs.CV

1604.07316 2016-04-26 cs.CV cs.LG cs.NE 79%

End to End Learning for Self-Driving Cars

Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, Karol Zieba

专题命中感知：self-driving(title,abstract)；分类 cs.CV

1505.00256 2015-09-29 cs.CV 79%

DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving

Chenyi Chen, Ari Seff, Alain Kornhauser, Jianxiong Xiao

专题命中感知：autonomous driving(title,abstract)；分类 cs.CV

1312.6024 2013-12-23 cs.CV 79%

Occupancy Detection in Vehicles Using Fisher Vector Image Representation

Yusuf Artan, Peter Paul

专题命中感知：occupancy(title,abstract)；分类 cs.CV

2608.05356 2026-08-13 cs.CV cs.RO 版本更新 79%

LoDA: A Level of Detection Aware Method and a Multimodal Sensing Benchmark for Object Level Change Detection

LoDA：一种面向目标级变化检测的检测级别感知方法及多模态感知基准

Haitian Wang, Xinyu Wang, Sheldon Fung, Xian Zhang, Zichen Geng

机构 * Western Australia Machine Intelligence Group Pty Ltd（西澳大利亚机器智能集团有限公司）； The University of Western Australia（西澳大利亚大学）； Curtin University（科廷大学）

专题命中感知：LiDAR(abstract,abstract_cn)；autonomous driving(abstract)；分类 cs.RO、cs.CV

AI总结该研究针对自动驾驶等领域的目标级变化检测问题，提出LoDA检测级别感知方法，构建LoDA基准，在Subiaco和Urb3DCD-V2基准上均超越现有最佳基线，提升了变化检测性能。

2608.03490 2026-08-05 cs.RO cs.CV 新提交 79%

Lightweight 3D Object Detection via Mamba-Based Knowledge Distillation

基于Mamba知识蒸馏的轻量型3D目标检测

Quoc Cuong Ninh, Huy Xuan Pham, Anh Tung Nguyen, Dinh Hoan Trinh

专题命中感知：LiDAR(abstract,abstract_cn)；autonomous driving(abstract)；分类 cs.RO、cs.CV

AI总结本研究提出基于Mamba的知识蒸馏框架，通过选择性体素空间特征对齐实现轻量型3D目标检测，在保持精度的同时显著降低计算负载。

Comments Accepted for publication in IEEE Robotics and Automation Letters (RA-L), 2026

2608.01572 2026-08-04 cs.CV cs.AI 新提交 79%

Enhancing Visual Perception in Foggy Conditions via Multiclass Fog Density Modeling

通过多类雾密度建模增强雾天条件下的视觉感知

Mohamad Mofeed Chaar, Galia Weidl

机构 * University of Applied Sciences, Aschaffenburg（阿沙芬堡应用科学大学）

专题命中感知：LiDAR(abstract,abstract_cn)；autonomous driving(abstract)；分类 cs.CV、cs.AI

AI总结本研究针对自动驾驶雾天感知难题，基于Waymo数据集合成雾数据，按五类雾密度训练专用感知模型，使特浓雾召回率提升15.6个百分点，验证了多专用模型策略的有效性。

Comments 8 pages, 5 figures,2 tables

2607.23910 2026-07-28 cs.CV cs.LG cs.MA cs.RO 新提交 79%

SimBEV2X: A Large-Scale Dataset and Data Generation Tool for Multi-Task Vehicle-to-Everything Cooperative Perception

SimBEV2X：用于多任务车联网协同感知的大规模数据集与数据生成工具

Goodarz Mehr, Sepideh Gohari, Montasir Abbas, Azim Eskandarian

专题命中感知：BEV(abstract)；LiDAR(abstract)；occupancy(abstract)；分类 cs.RO、cs.CV

AI总结研究针对V2X协同感知算法发展受限问题，介绍基于CARLA模拟器的SimBEV2X数据生成工具及数据集，通过它建立基线并提出CoBEVFusion架构，实现上下文感知多智能体特征聚合，性能优越。

Comments Submitted to IEEE for review

1. 感知 6057 篇

Towards Corner Case Detection for Autonomous Driving

Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving

Forest Tree Detection and Segmentation using High Resolution Airborne LiDAR

An FPGA-Accelerated Design for Deep Learning Pedestrian Detection in Self-Driving Vehicles

A Brief Survey and an Application of Semantic Image Segmentation for Autonomous Driving

Multisensor Online Transfer Learning for 3D LiDAR-based Human Detection with a Mobile Robot

Textual Explanations for Self-Driving Vehicles

LaneNet: Real-Time Lane Detection Networks for Autonomous Driving

Deep Object Tracking on Dynamic Occupancy Grid Maps Using RNNs

BirdNet: a 3D Object Detection Framework from LiDAR information

Synchronous Adversarial Feature Learning for LiDAR based Loop Closure Detection

Towards Stable Adversarial Feature Learning for LiDAR based Loop Closure Detection

Real-Time Road Segmentation Using LiDAR Data Processing on an FPGA

Cone Detection using a Combination of LiDAR and Vision-based Machine Learning

Characterization of a RS-LiDAR for 3D Perception

3D Visual Perception for Self-Driving Cars using a Multi-Camera System: Calibration, Mapping, Localization, and Obstacle Detection

Interpretable Learning for Self-Driving Cars by Visualizing Causal Attention

Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks

A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data

A Statistical Method for Parking Spaces Occupancy Detection via Automotive Radars

Autonomous driving challenge: To Infer the property of a dynamic object based on its motion pattern using recurrent neural network

Can we unify monocular detectors for autonomous driving by using the pixel-wise semantic segmentation of CNNs?

Instance-Level Segmentation for Autonomous Driving with Deep Densely Connected MRFs

End to End Learning for Self-Driving Cars

DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving

Occupancy Detection in Vehicles Using Fisher Vector Image Representation

LoDA: A Level of Detection Aware Method and a Multimodal Sensing Benchmark for Object Level Change Detection

Lightweight 3D Object Detection via Mamba-Based Knowledge Distillation

Enhancing Visual Perception in Foggy Conditions via Multiclass Fog Density Modeling

SimBEV2X: A Large-Scale Dataset and Data Generation Tool for Multi-Task Vehicle-to-Everything Cooperative Perception