自动驾驶 - arXivDaily 专题

1711.06396 2017-11-20 cs.CV 57%

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

Yin Zhou, Oncel Tuzel

专题命中感知：LiDAR(abstract)；分类 cs.CV

1711.05491 2017-11-16 cs.CV 57%

Squeeze-SegNet: A new fast Deep Convolutional Neural Network for Semantic Segmentation

Geraldin Nanfack, Azeddine Elhassouny, Rachid Oulad Haj Thami

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

Comments The 10th International Conference on Machine Vision (ICMV 2017). arXiv admin note: text overlap with arXiv:1704.06857 by other authors

1709.03526 2017-11-13 cs.RO 57%

FieldSAFE: Dataset for Obstacle Detection in Agriculture

Mikkel Fly Kragh, Peter Christiansen, Morten Stigaard Laursen, Morten Larsen, Kim Arild Steen, Ole Green, Henrik Karstoft, Rasmus Nyholm Jørgensen

专题命中感知：LiDAR(abstract)；分类 cs.RO

Comments Submitted to special issue of MDPI Sensors: Sensors in Agriculture

Journal ref Sensors 2017, 17(11), 2579

1604.03351 2017-10-23 cs.CV cs.NE 57%

Orientation-boosted Voxel Nets for 3D Object Recognition

Nima Sedaghat, Mohammadreza Zolfaghari, Ehsan Amiri, Thomas Brox

专题命中感知：LiDAR(abstract)；分类 cs.CV

Comments BMVC'17 version. Added some experiments + auto-alignment of Modelnet40

1707.08313 2017-10-09 cs.CV 57%

Cascaded Scene Flow Prediction using Semantic Segmentation

Zhile Ren, Deqing Sun, Jan Kautz, Erik B. Sudderth

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

Comments International Conference on 3D Vision (3DV), 2017 (oral presentation)

1709.08518 2017-09-26 cs.RO 57%

A View-Dependent Adaptive Matched Filter for LADAR-Based Vehicle Tracking

Daniel D. Morris, Regis Hoffman, Paul Haley

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

Comments Proc. of 14th IASTED Int. Conf. on Robotics and Applications, Cambridge, MA, USA, Nov 2-4, 2009

1709.03138 2017-09-12 cs.CV 57%

Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps (Masters Thesis)

Florian Piewak

专题命中感知：occupancy(abstract)；分类 cs.CV

Comments This is the masters thesis of Florian Piewak. A shorter version of this thesis was accepted at IV 2017

1708.02813 2017-08-10 cs.CV 57%

BlitzNet: A Real-Time Deep Network for Scene Understanding

Nikita Dvornik, Konstantin Shmelkov, Julien Mairal, Cordelia Schmid

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

1708.02421 2017-08-09 cs.CV 57%

FoveaNet: Perspective-aware Urban Scene Parsing

Xin Li, Zequn Jie, Wei Wang, Changsong Liu, Jimei Yang, Xiaohui Shen, Zhe Lin, Qiang Chen, Shuicheng Yan, Jiashi Feng

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

1703.07684 2017-08-09 cs.CV cs.LG 57%

Predicting Deeper into the Future of Semantic Segmentation

Pauline Luc, Natalia Neverova, Camille Couprie, Jakob Verbeek, Yann LeCun

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

Comments Accepted to ICCV 2017. Supplementary material available on the authors' webpages

1702.04593 2017-07-25 cs.CV 57%

Deep Multi-camera People Detection

Tatjana Chavdarova, François Fleuret

专题命中感知：occupancy(abstract)；分类 cs.CV

1605.09410 2017-07-14 cs.LG cs.CV 57%

End-to-End Instance Segmentation with Recurrent Attention

Mengye Ren, Richard S. Zemel

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

Comments CVPR 2017

1706.04041 2017-07-12 cs.CV 57%

Text Extraction From Texture Images Using Masked Signal Decomposition

Shervin Minaee, Yao Wang

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

Comments arXiv admin note: text overlap with arXiv:1704.07711

1706.08564 2017-06-28 cs.CV 57%

Illuminating Pedestrians via Simultaneous Detection & Segmentation

Garrick Brazil, Xi Yin, Xiaoming Liu

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

1706.04353 2017-06-15 cs.RO 57%

Multi-Lane Perception Using Feature Fusion Based on GraphSLAM

Alexey Abramov, Christopher Bayer, Claudio Heller, Claudia Loy

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

1706.01631 2017-06-07 cs.RO 57%

A Flexible Modeling Approach for Robust Multi-Lane Road Estimation

Alexey Abramov, Christopher Bayer, Claudio Heller, Claudia Loy

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

1705.08624 2017-05-25 cs.CV 57%

VANETs Meet Autonomous Vehicles: A Multimodal 3D Environment Learning Approach

Yassine Maalej, Sameh Sorour, Ahmed Abdel-Rahim, Mohsen Guizani

专题命中感知：LiDAR(abstract)；分类 cs.CV

Comments 7 pages, 12 figures

1705.06057 2017-05-18 cs.CV cs.NE 57%

Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps

Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre

专题命中感知：LiDAR(abstract)；分类 cs.CV

Journal ref EARTHVISION 2017 IEEE/ISPRS CVPR Workshop. Large Scale Computer Vision for Remote Sensing Imagery, Jul 2017, Honolulu, United States. 2017

1610.06940 2017-05-08 cs.AI cs.LG stat.ML 57%

Safety Verification of Deep Neural Networks

Xiaowei Huang, Marta Kwiatkowska, Sen Wang, Min Wu

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

Comments To appear as invited paper at CAV 2017

1510.03608 2017-04-27 cs.CV 57%

Deep convolutional neural networks for pedestrian detection

Denis Tomè, Federico Monti, Luca Baroffio, Luca Bondi, Marco Tagliasacchi, Stefano Tubaro

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

Comments submitted to Elsevier Signal Processing: Image Communication special Issue on Deep Learning

1703.02145 2017-03-08 cs.RO 57%

Dynamic Arrival Rate Estimation for Campus Mobility on Demand Network Graphs

Justin Miller, Andres Hasfura, Shih-Yuan Liu, Jonathan P. How

专题命中感知：LiDAR(abstract)；分类 cs.RO

Comments Appears in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). http://ieeexplore.ieee.org/abstract/document/7759357/

Journal ref IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, 2016, pp. 2285-2292 (2016)

1701.04350 2017-01-17 cs.RO 57%

An Object-oriented approach to Robotic planning using Taxi domain

Aasheesh Singh

专题命中感知：LiDAR(abstract)；分类 cs.RO

Comments Standard 4 page IEEE Format Submitted in IEEE-DTU Technical Journal IOTA

1612.04340 2016-12-14 stat.ML cs.LG cs.RO 57%

End-to-End Deep Reinforcement Learning for Lane Keeping Assist

Ahmad El Sallab, Mohammed Abdou, Etienne Perot, Senthil Yogamani

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

Comments Presented at the Machine Learning for Intelligent Transportation Systems Workshop, NIPS 2016

1611.08323 2016-12-07 cs.CV 57%

Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes

Tobias Pohlen, Alexander Hermans, Markus Mathias, Bastian Leibe

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

Comments Changes in v2: Fixed equation (10), fixed legend of Figure 6, fixed legend of Figure 9, added page numbers, fixed minor spelling mistakes

1412.7006 2016-11-15 cs.CV cs.LG cs.NE 57%

Multi-modal Sensor Registration for Vehicle Perception via Deep Neural Networks

Michael Giering, Vivek Venugopalan, Kishore Reddy

专题命中感知：LiDAR(abstract)；分类 cs.CV

Comments 7 pages, double column, IEEE format, accepted at IEEE HPEC 2015

1611.02644 2016-11-09 cs.CV 57%

Multispectral Deep Neural Networks for Pedestrian Detection

Jingjing Liu, Shaoting Zhang, Shu Wang, Dimitris N. Metaxas

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

Comments 13 pages, 8 figures, BMVC 2016 oral

1610.03651 2016-10-13 cs.RO 57%

Efficient Probabilistic Collision Detection for Non-Convex Shapes

Jae Sung Park, Chonhyon Park, Dinesh Manocha

专题命中感知：trajectory planning(abstract)；分类 cs.RO

Comments 9 pages, 6 figures

1604.03755 2016-09-13 cs.CV cs.GR 57%

VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

Abhishek Sharma, Oliver Grau, Mario Fritz

专题命中感知：occupancy(abstract)；分类 cs.CV

1604.01827 2016-08-24 cs.CV 57%

Exploiting Semantic Information and Deep Matching for Optical Flow

Min Bai, Wenjie Luo, Kaustav Kundu, Raquel Urtasun

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

1602.03930 2016-08-16 cs.CV 57%

Global Deconvolutional Networks for Semantic Segmentation

Vladimir Nekrasov, Janghoon Ju, Jaesik Choi

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

Comments BMVC 2016 Conference

1. 感知 6065 篇

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

Squeeze-SegNet: A new fast Deep Convolutional Neural Network for Semantic Segmentation

FieldSAFE: Dataset for Obstacle Detection in Agriculture

Orientation-boosted Voxel Nets for 3D Object Recognition

Cascaded Scene Flow Prediction using Semantic Segmentation

A View-Dependent Adaptive Matched Filter for LADAR-Based Vehicle Tracking

Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps (Masters Thesis)

BlitzNet: A Real-Time Deep Network for Scene Understanding

FoveaNet: Perspective-aware Urban Scene Parsing

Predicting Deeper into the Future of Semantic Segmentation

Deep Multi-camera People Detection

End-to-End Instance Segmentation with Recurrent Attention

Text Extraction From Texture Images Using Masked Signal Decomposition

Illuminating Pedestrians via Simultaneous Detection & Segmentation

Multi-Lane Perception Using Feature Fusion Based on GraphSLAM

A Flexible Modeling Approach for Robust Multi-Lane Road Estimation

VANETs Meet Autonomous Vehicles: A Multimodal 3D Environment Learning Approach

Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps

Safety Verification of Deep Neural Networks

Deep convolutional neural networks for pedestrian detection

Dynamic Arrival Rate Estimation for Campus Mobility on Demand Network Graphs

An Object-oriented approach to Robotic planning using Taxi domain

End-to-End Deep Reinforcement Learning for Lane Keeping Assist

Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes

Multi-modal Sensor Registration for Vehicle Perception via Deep Neural Networks

Multispectral Deep Neural Networks for Pedestrian Detection

Efficient Probabilistic Collision Detection for Non-Convex Shapes

VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

Exploiting Semantic Information and Deep Matching for Optical Flow

Global Deconvolutional Networks for Semantic Segmentation