暂无分享,去创建一个
[1] Frank Dellaert,et al. Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing , 2006, Int. J. Robotics Res..
[2] Dieter Fox,et al. DynamicFusion: Reconstruction and tracking of non-rigid scenes in real-time , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Andrew J. Davison,et al. Real-Time Camera Tracking: When is High Frame-Rate Best? , 2012, ECCV.
[4] Steve B. Furber,et al. The SpiNNaker Project , 2014, Proceedings of the IEEE.
[5] Steven Lovegrove,et al. Parametric dense visual SLAM , 2011 .
[6] Dieter Fox,et al. Self-Supervised Visual Descriptor Learning for Dense Correspondence , 2017, IEEE Robotics and Automation Letters.
[7] Paul H. J. Kelly,et al. SLAM++: Simultaneous Localisation and Mapping at the Level of Objects , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[8] Frank Arens,et al. [Welcome to the Jungle]. , 2014, Pflege Zeitschrift.
[9] Wolfram Burgard,et al. A benchmark for the evaluation of RGB-D SLAM systems , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[10] Stefan Leutenegger,et al. Semantic Texture for Robust Dense Tracking , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).
[11] Dieter Fox,et al. DA-RNN: Semantic Mapping with Data Associated Recurrent Neural Networks , 2017, Robotics: Science and Systems.
[12] Randy H. Katz,et al. A Berkeley View of Systems Challenges for AI , 2017, ArXiv.
[13] Michael Bosse,et al. Keyframe-based visual–inertial odometry using nonlinear optimization , 2015, Int. J. Robotics Res..
[14] Stefan Leutenegger,et al. SemanticFusion: Dense 3D semantic mapping with convolutional neural networks , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[15] Rahul Sukthankar,et al. Cognitive Mapping and Planning for Visual Navigation , 2017, International Journal of Computer Vision.
[16] Kurt Konolige,et al. Sparse Sparse Bundle Adjustment , 2010, BMVC.
[17] Andrew Zisserman,et al. Spatial Transformer Networks , 2015, NIPS.
[18] Stefan Leutenegger,et al. ElasticFusion: Dense SLAM Without A Pose Graph , 2015, Robotics: Science and Systems.
[19] Federico Tombari,et al. CNN-SLAM: Real-Time Dense Monocular SLAM with Learned Depth Prediction , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Daniel Cremers,et al. LSD-SLAM: Large-Scale Direct Monocular SLAM , 2014, ECCV.
[21] Paul H. J. Kelly,et al. Algorithmic Performance-Accuracy Trade-off in 3D Vision Applications Using HyperMapper , 2017, 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).
[22] Michael F. P. O'Boyle,et al. SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Visual SLAM , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[23] Olivier Stasse,et al. MonoSLAM: Real-Time Single Camera SLAM , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[24] G. Klein,et al. Parallel Tracking and Mapping for Small AR Workspaces , 2007, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.
[25] Andrew J. Davison,et al. Real-time simultaneous localisation and mapping with a single camera , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[26] Davide Scaramuzza,et al. SVO: Fast semi-direct monocular visual odometry , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[27] Kurt Konolige,et al. FrameSLAM: From Bundle Adjustment to Real-Time Visual Mapping , 2008, IEEE Transactions on Robotics.
[28] Judea Pearl,et al. Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution , 2018, WSDM.
[29] Andrew W. Fitzgibbon,et al. KinectFusion: Real-time dense surface mapping and tracking , 2011, 2011 10th IEEE International Symposium on Mixed and Augmented Reality.
[30] Horst Bischof,et al. Real-time Computation of Variational Methods on Graphics Hardware , 2007 .
[31] Stefan Leutenegger,et al. CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[32] Andrew J. Davison,et al. Active search for real-time vision , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[33] Matthias Nießner,et al. ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Takeo Kanade,et al. An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.
[35] Andrew J. Davison,et al. Transferring End-to-End Visuomotor Control from Simulation to Real World for a Multi-Stage Task , 2017, CoRL.
[36] Stefan Leutenegger,et al. Monocular, Real-Time Surface Reconstruction Using Dynamic Level of Detail , 2016, 2016 Fourth International Conference on 3D Vision (3DV).
[37] Andrew J. Davison,et al. A benchmark for RGB-D visual odometry, 3D reconstruction and SLAM , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[38] Andrew J. Davison,et al. Automatically and efficiently inferring the hierarchical structure of visual maps , 2009, 2009 IEEE International Conference on Robotics and Automation.
[39] J. Pearl. Theoretical Impediments to Machine Learning A position paper , 2016 .
[40] Ian D. Reid,et al. RSLAM: A System for Large-Scale Mapping in Constant-Time Using Stereo , 2011, International Journal of Computer Vision.
[41] Noah Snavely,et al. Unsupervised Learning of Depth and Ego-Motion from Video , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Andrew J. Davison,et al. DTAM: Dense tracking and mapping in real-time , 2011, 2011 International Conference on Computer Vision.
[43] Dana H. Ballard,et al. Animate Vision , 1991, Artif. Intell..
[44] Viorica Patraucean,et al. gvnn: Neural Network Library for Geometric Computer Vision , 2016, ECCV Workshops.
[45] Wolfram Burgard,et al. OctoMap : A Probabilistic , Flexible , and Compact 3 D Map Representation for Robotic Systems , 2010 .
[46] Sen Wang,et al. DeepVO: Towards end-to-end visual odometry with deep Recurrent Convolutional Neural Networks , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[47] J. M. M. Montiel,et al. ORB-SLAM: A Versatile and Accurate Monocular SLAM System , 2015, IEEE Transactions on Robotics.
[48] Michael F. P. O'Boyle,et al. Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM , 2014, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[49] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[50] Richard A. Newcombe,et al. Dense visual SLAM , 2012 .
[51] Paul H. J. Kelly,et al. Application-oriented design space exploration for SLAM algorithms , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[52] John Markoff,et al. Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots , 2015 .
[53] Lourdes Agapito,et al. Co-fusion: Real-time segmentation, tracking and fusion of multiple objects , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[54] Sergey Levine,et al. Deep spatial autoencoders for visuomotor learning , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[55] Stefan Leutenegger,et al. SceneNet RGB-D: Can 5M Synthetic Images Beat Generic ImageNet Pre-training on Indoor Segmentation? , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[56] Frank Dellaert,et al. iSAM2: Incremental smoothing and mapping using the Bayes tree , 2012, Int. J. Robotics Res..
[57] Tom Drummond,et al. Machine Learning for High-Speed Corner Detection , 2006, ECCV.
[58] Piotr Dudek,et al. Vision Chips with In-pixel Processors for High-performance Low-power Embedded Vision Systems , 2016 .
[59] Stefan Leutenegger,et al. Real-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera , 2016, ECCV.