Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry
暂无分享,去创建一个
Hongbin Zha | Fei Xue | Xin Wang | Shunkai Li | Junqiu Wang | Qiuyuan Wang | H. Zha | Xin Wang | Junqiu Wang | Shunkai Li | Qiuyuan Wang | Fei Xue
[1] Thomas Brox,et al. FlowNet: Learning Optical Flow with Convolutional Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[2] Andrea Vedaldi,et al. MapNet: An Allocentric Spatial Memory for Mapping Environments , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[3] K. Madhava Krishna,et al. Geometric Consistency for Self-Supervised End-to-End Visual Odometry , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[4] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[5] Ian D. Reid,et al. Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[6] Torsten Sattler,et al. VSO: Visual Semantic Odometry , 2018, ECCV.
[7] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[8] Noah Snavely,et al. Unsupervised Learning of Depth and Ego-Motion from Video , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .
[10] Ethan Rublee,et al. ORB: An efficient alternative to SIFT or SURF , 2011, 2011 International Conference on Computer Vision.
[11] Daniel Cremers,et al. Direct Sparse Odometry , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[12] Andrew J. Davison,et al. DTAM: Dense tracking and mapping in real-time , 2011, 2011 International Conference on Computer Vision.
[13] Sean L. Bowman,et al. Probabilistic data association for semantic SLAM , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[14] Jörg Stückler,et al. Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry , 2018, ECCV.
[15] Zhichao Yin,et al. GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[16] Qijun Chen,et al. Scale Recovery for Monocular Visual Odometry Using Depth Estimated with Deep Convolutional Neural Fields , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[17] Sen Wang,et al. End-to-end, sequence-to-sequence probabilistic visual odometry through deep neural networks , 2018, Int. J. Robotics Res..
[18] Thomas Brox,et al. DeepTAM: Deep Tracking and Mapping , 2018, ECCV.
[19] Dongbing Gu,et al. UnDeepVO: Monocular Visual Odometry Through Unsupervised Deep Learning , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[20] 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.
[21] Jan Kautz,et al. Geometry-Aware Learning of Maps for Camera Localization , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[22] Jian Zhang,et al. Global Pose Estimation with an Attention-Based Recurrent Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[23] 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).
[24] Thomas Brox,et al. DeMoN: Depth and Motion Network for Learning Monocular Stereo , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] 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).
[26] Anelia Angelova,et al. Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[27] Jason Weston,et al. End-To-End Memory Networks , 2015, NIPS.
[28] 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.
[29] Juan D. Tardós,et al. ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras , 2016, IEEE Transactions on Robotics.
[30] Jitendra Malik,et al. Learning to See by Moving , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[31] Julius Ziegler,et al. StereoScan: Dense 3d reconstruction in real-time , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).
[32] Dit-Yan Yeung,et al. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting , 2015, NIPS.
[33] Andreas Geiger,et al. Are we ready for autonomous driving? The KITTI vision benchmark suite , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[34] Hujun Bao,et al. ICE-BA: Incremental, Consistent and Efficient Bundle Adjustment for Visual-Inertial SLAM , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[35] Daniel Cremers,et al. LSD-SLAM: Large-Scale Direct Monocular SLAM , 2014, ECCV.
[36] Daniel Cremers,et al. Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[37] Hongbin Zha,et al. Guided Feature Selection for Deep Visual Odometry , 2018, ACCV.
[38] A. Markham,et al. - Temporal Model for 6-DoF VideoClip Relocalization , 2022 .
[39] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.