自动驾驶 - arXivDaily 专题

1803.06459 2018-03-20 cs.CV cs.AI cs.LG 62%

Learning to Cluster for Proposal-Free Instance Segmentation

Yen-Chang Hsu, Zheng Xu, Zsolt Kira, Jiawei Huang

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

1803.00387 2018-03-02 cs.CV eess.IV stat.ML 62%

A General Pipeline for 3D Detection of Vehicles

Xinxin Du, Marcelo H. Ang, Sertac Karaman, Daniela Rus

专题命中感知：autonomous driving(abstract)；分类 cs.CV、eess.IV

Comments Accepted at ICRA 2018

1612.03653 2017-09-22 cs.AI cs.RO 62%

Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks

Sahand Sharifzadeh, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers

专题命中感知：autonomous driving(abstract)；分类 cs.RO、cs.AI

Comments NIPS workshop on Deep Learning for Action and Interaction, 2016

1709.04751 2017-09-15 cs.RO cs.CV cs.LG 62%

From Plants to Landmarks: Time-invariant Plant Localization that uses Deep Pose Regression in Agricultural Fields

Florian Kraemer, Alexander Schaefer, Andreas Eitel, Johan Vertens, Wolfram Burgard

专题命中感知：LiDAR(abstract)；分类 cs.RO、cs.CV

Comments IROS 2017 AGROB Workshop

1708.02330 2017-08-14 cs.RO cs.CV 62%

What Makes a Place? Building Bespoke Place Dependent Object Detectors for Robotics

Jeffrey Hawke, Alex Bewley, Ingmar Posner

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

Comments IROS 2017

1704.06857 2017-04-25 cs.CV cs.AI 62%

A Review on Deep Learning Techniques Applied to Semantic Segmentation

Alberto Garcia-Garcia, Sergio Orts-Escolano, Sergiu Oprea, Victor Villena-Martinez, Jose Garcia-Rodriguez

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

Comments Submitted to TPAMI on Apr. 22, 2017

1610.01983 2017-02-28 cs.CV cs.RO 62%

Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?

Matthew Johnson-Roberson, Charles Barto, Rounak Mehta, Sharath Nittur Sridhar, Karl Rosaen, Ram Vasudevan

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

Comments Proceedings of International Conference on Robotics and Automation (ICRA) 2017, 8 pages

1701.08449 2017-01-31 cs.RO cs.CV 62%

SafeDrive: A Robust Lane Tracking System for Autonomous and Assisted Driving Under Limited Visibility

Junaed Sattar, Jiawei Mo

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

1610.09609 2016-11-01 cs.CV cs.AI cs.NE 62%

Generalized Haar Filter based Deep Networks for Real-Time Object Detection in Traffic Scene

Keyu Lu, Jian Li, Xiangjing An, Hangen He

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

1609.09468 2016-09-30 cs.CV cs.RO 62%

Reconstructing Vechicles from a Single Image: Shape Priors for Road Scene Understanding

J. Krishna Murthy, G. V. Sai Krishna, Falak Chhaya, K. Madhava Krishna

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

1609.00017 2016-09-02 cs.RO cs.CV 62%

Radiation Search Operations using Scene Understanding with Autonomous UAV and UGV

Gordon Christie, Adam Shoemaker, Kevin Kochersberger, Pratap Tokekar, Lance McLean, Alexander Leonessa

专题命中感知：LiDAR(abstract)；分类 cs.RO、cs.CV

1604.00449 2016-04-05 cs.CV cs.AI 62%

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

Christopher B. Choy, Danfei Xu, JunYoung Gwak, Kevin Chen, Silvio Savarese

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

Comments Appendix can be found at http://cvgl.stanford.edu/papers/choy_16_appendix.pdf

1504.01716 2015-04-20 cs.RO cs.CV 62%

An Empirical Evaluation of Deep Learning on Highway Driving

Brody Huval, Tao Wang, Sameep Tandon, Jeff Kiske, Will Song, Joel Pazhayampallil, Mykhaylo Andriluka, Pranav Rajpurkar, Toki Migimatsu, Royce Cheng-Yue, Fernando Mujica, Adam Coates, Andrew Y. Ng

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

Comments Added a video for lane detection

2301.05711 2025-09-03 cs.CV 61%

OA-DET3D: Embedding Object Awareness as a General Plug-in for Multi-Camera 3D Object Detection

Xiaomeng Chu, Jiajun Deng, Jianmin Ji, Yu Zhang, Houqiang Li, Yanyong Zhang

机构 * University of Science and Technology of China（科学技术大学）； The University of Sydney（悉尼大学）

专题命中感知：BEV(abstract,comments)；分类 cs.CV

Comments Accepted by IJCV after more than two years of reviewing. Original title: OA-BEV: Bringing Object Awareness to Bird's-Eye-View Representation for Multi-Camera 3D Object Detection

2502.12208 2025-07-09 cs.SE cs.RO 61%

AI-Augmented Metamorphic Testing for Comprehensive Validation of Autonomous Vehicles

Tony Zhang, Burak Kantarci, Umair Siddique

机构 * School of Electrical Engineering and Computer Science（电气工程与计算机科学学院）； reasonX Labs Inc.（reasonX实验室）

专题命中感知：self-driving(abstract)；分类 cs.RO；autonomous driving(comments)

Comments 4 pages, 2 figures, Accepted to 1st International Workshop on Software Engineering for Autonomous Driving Systems (SE4ADS 2025) in 47th International Conference on Software Engineering (ICSE) 2025

2504.18773 2025-04-29 cs.CV 61%

Depth as Points: Center Point-based Depth Estimation

Zhiheng Tu, Xinjian Huang, Yong He, Ruiyang Zhou, Bo Du, Weitao Wu

机构 * School of Mechanical Engineering, Nanjing University of Science and Technology（机械工程学院，南京理工大学）； School of Cyber Science and Engineering, Nanjing University of Science and Technology（网络科学与工程学院，南京理工大学）； School of Computer Science , Wuhan University（计算机科学学院，武汉大学）

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

Comments Depth Esitimation, Key-points, Virtual Datasets, Autonomous Driving

2304.06547 2024-11-12 cs.CV 61%

RadarGNN: Transformation Invariant Graph Neural Network for Radar-based Perception

Felix Fent, Philipp Bauerschmidt, Markus Lienkamp

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

Comments Accepted to CVPR 2023 Workshop on Autonomous Driving (WAD)

2102.06777 2024-09-04 cs.CV cs.LG 61%

INSTA-YOLO: Real-Time Instance Segmentation

Eslam Mohamed, Abdelrahman Shaker, Ahmad El-Sallab, Mayada Hadhoud

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

Comments Accepted at ICML-2020 Workshop on AI for Autonomous Driving

2006.07802 2024-01-18 cs.CV 61%

Geometry-Aware Instance Segmentation with Disparity Maps

Cho-Ying Wu, Xiaoyan Hu, Michael Happold, Qiangeng Xu, Ulrich Neumann

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

Comments CVPR 2020 Workshop of Scalability in Autonomous Driving (WSAD). Please refer to WSAD site for details; fix typos

2310.06753 2023-11-02 cs.CV 61%

TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning

Dongming Wu, Jiahao Chang, Fan Jia, Yingfei Liu, Tiancai Wang, Jianbing Shen

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

Comments The 1st solution for 1st OpenLane Topology in Autonomous Driving Challenge. Code is at https://github.com/wudongming97/TopoMLP

2307.07147 2023-07-17 cs.CV 61%

Linking vision and motion for self-supervised object-centric perception

Kaylene C. Stocking, Zak Murez, Vijay Badrinarayanan, Jamie Shotton, Alex Kendall, Claire Tomlin, Christopher P. Burgess

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

Comments Presented at the CVPR 2023 Vision-Centric Autonomous Driving workshop

2305.18452 2023-05-31 cs.CV cs.LG 61%

Generating Driving Scenes with Diffusion

Ethan Pronovost, Kai Wang, Nick Roy

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

Comments Accepted to the ICRA Scalable Autonomous Driving Workshop

2304.02991 2023-04-07 cs.CV 61%

Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic Segmentation

Adriano Cardace, Pierluigi Zama Ramirez, Samuele Salti, Luigi Di Stefano

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

Comments Accepted at the CVPR2023 Workshop on Autonomous Driving (WAD)

2206.10692 2022-11-10 cs.CV cs.LG 61%

Multi-level Domain Adaptation for Lane Detection

Chenguang Li, Boheng Zhang, Jia Shi, Guangliang Cheng

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

Comments Proceedings of the CVPR 2022 Workshop of Autonomous Driving

2210.16204 2022-10-31 cs.CV 61%

TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM

Nicola Marinello, Marc Proesmans, Luc Van Gool

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

Comments Accepted to CVPR 2022 Workshop on Autonomous Driving

Journal ref Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops June 2022 4500-4510

2110.15074 2021-10-29 cs.CV 61%

Meta Guided Metric Learner for Overcoming Class Confusion in Few-Shot Road Object Detection

Anay Majee, Anbumani Subramanian, Kshitij Agrawal

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

Comments Accepted to NeurIPS 2021 Workshop on Machine Learning For Autonomous Driving, 12 pages, 6 figures

2106.11422 2021-06-23 cs.CV cs.LG 61%

MODETR: Moving Object Detection with Transformers

Eslam Mohamed, Ahmad El-Sallab

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

Journal ref Machine Learning for Autonomous Driving Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada

2009.11859 2020-09-25 cs.CV cs.LG 61%

Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection

Yue Wang, Alireza Fathi, Jiajun Wu, Thomas Funkhouser, Justin Solomon

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

Comments The Workshop on Perception for Autonomous Driving at ECCV2020

1908.11757 2019-09-02 cs.CV cs.LG 61%

Temporal Coherence for Active Learning in Videos

Javad Zolfaghari Bengar, Abel Gonzalez-Garcia, Gabriel Villalonga, Bogdan Raducanu, Hamed H. Aghdam, Mikhail Mozerov, Antonio M. Lopez, Joost van de Weijer

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

Comments Accepted at ICCVW 2019 (CVRSUAD-Road Scene Understanding and Autonomous Driving)

1904.08492 2019-04-23 cs.CV 61%

MultiNet++: Multi-Stream Feature Aggregation and Geometric Loss Strategy for Multi-Task Learning

Sumanth Chennupati, Ganesh Sistu, Senthil Yogamani, Samir A Rawashdeh

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

Comments Accepted for CVPR 2019 Workshop on Autonomous Driving (WAD). Demo Video can be accessed at https://youtu.be/E378PzLq7lQ

1. 感知 6065 篇

Learning to Cluster for Proposal-Free Instance Segmentation

A General Pipeline for 3D Detection of Vehicles

Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks

From Plants to Landmarks: Time-invariant Plant Localization that uses Deep Pose Regression in Agricultural Fields

What Makes a Place? Building Bespoke Place Dependent Object Detectors for Robotics

A Review on Deep Learning Techniques Applied to Semantic Segmentation

Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?

SafeDrive: A Robust Lane Tracking System for Autonomous and Assisted Driving Under Limited Visibility

Generalized Haar Filter based Deep Networks for Real-Time Object Detection in Traffic Scene

Reconstructing Vechicles from a Single Image: Shape Priors for Road Scene Understanding

Radiation Search Operations using Scene Understanding with Autonomous UAV and UGV

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

An Empirical Evaluation of Deep Learning on Highway Driving

OA-DET3D: Embedding Object Awareness as a General Plug-in for Multi-Camera 3D Object Detection

AI-Augmented Metamorphic Testing for Comprehensive Validation of Autonomous Vehicles

Depth as Points: Center Point-based Depth Estimation

RadarGNN: Transformation Invariant Graph Neural Network for Radar-based Perception

INSTA-YOLO: Real-Time Instance Segmentation

Geometry-Aware Instance Segmentation with Disparity Maps

TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning

Linking vision and motion for self-supervised object-centric perception

Generating Driving Scenes with Diffusion

Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic Segmentation

Multi-level Domain Adaptation for Lane Detection

TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM

Meta Guided Metric Learner for Overcoming Class Confusion in Few-Shot Road Object Detection

MODETR: Moving Object Detection with Transformers

Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection

Temporal Coherence for Active Learning in Videos

MultiNet++: Multi-Stream Feature Aggregation and Geometric Loss Strategy for Multi-Task Learning