Unsupervised framework for depth estimation and camera motion prediction from video
暂无分享,去创建一个
Dongbing Gu | Xiafu Peng | Huosheng Hu | Xunyu Zhong | Delong Yang | Huosheng Hu | Dongbing Gu | Xiafu Peng | Xunyu Zhong | Delong Yang
[1] Sinisa Todorovic,et al. Monocular Depth Estimation Using Neural Regression Forest , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Meng Wang,et al. 2D-to-3D image conversion by learning depth from examples , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[3] Nassir Navab,et al. Deeper Depth Prediction with Fully Convolutional Residual Networks , 2016, 2016 Fourth International Conference on 3D Vision (3DV).
[4] Rob Fergus,et al. Depth Map Prediction from a Single Image using a Multi-Scale Deep Network , 2014, NIPS.
[5] Noah Snavely,et al. Unsupervised Learning of Depth and Ego-Motion from Video , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] 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.
[7] Jürgen Sturm,et al. Evaluating Egomotion and Structure-from-Motion Approaches Using the TUM RGB-D Benchmark , 2012 .
[8] Sebastian Ramos,et al. The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[10] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[11] 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.
[12] Hu Tian,et al. Depth estimation with convolutional conditional random field network , 2016, Neurocomputing.
[13] Andrea Soltoggio,et al. Online Representation Learning with Single and Multi-layer Hebbian Networks for Image Classification , 2017, ICANN.
[14] Jörg Stückler,et al. Semi-Supervised Deep Learning for Monocular Depth Map Prediction , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Richard Szeliski,et al. High-accuracy stereo depth maps using structured light , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[16] Ali Farhadi,et al. Deep3D: Fully Automatic 2D-to-3D Video Conversion with Deep Convolutional Neural Networks , 2016, ECCV.
[17] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] 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).
[19] Nicu Sebe,et al. Unsupervised Adversarial Depth Estimation Using Cycled Generative Networks , 2018, 2018 International Conference on 3D Vision (3DV).
[20] Jianxiong Xiao,et al. DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[21] Jun Li,et al. A Two-Streamed Network for Estimating Fine-Scaled Depth Maps from Single RGB Images , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[22] Ce Liu,et al. Depth Extraction from Video Using Non-parametric Sampling , 2012, ECCV.
[23] Dongbing Gu,et al. UnDeepVO: Monocular Visual Odometry Through Unsupervised Deep Learning , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[24] Raquel Urtasun,et al. Efficient Deep Learning for Stereo Matching , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Simei Gomes Wysoski,et al. Fast and adaptive network of spiking neurons for multi-view visual pattern recognition , 2008, Neurocomputing.
[26] Andrew Owens,et al. SUN3D: A Database of Big Spaces Reconstructed Using SfM and Object Labels , 2013, 2013 IEEE International Conference on Computer Vision.
[27] Oisin Mac Aodha,et al. Unsupervised Monocular Depth Estimation with Left-Right Consistency , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Yuan Gao,et al. Exploiting Symmetry and/or Manhattan Properties for 3D Object Structure Estimation from Single and Multiple Images , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] M. W. Shields,et al. A theoretical framework for multiple neural network systems , 2008, Neurocomputing.
[30] Jitendra Malik,et al. Multi-view Consistency as Supervisory Signal for Learning Shape and Pose Prediction , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[31] Junjun Jiang,et al. Robust Feature Matching for Remote Sensing Image Registration via Locally Linear Transforming , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[32] Friedrich Fraundorfer,et al. Topological mapping, localization and navigation using image collections , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[33] Rob Fergus,et al. Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[34] F. Helmchen,et al. Imaging cellular network dynamics in three dimensions using fast 3D laser scanning , 2007, Nature Methods.
[35] Chunhua Shen,et al. Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[36] Konstantinos G. Derpanis,et al. Back to Basics: Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness , 2016, ECCV Workshops.
[37] Dacheng Tao,et al. Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[38] Guosheng Lin,et al. Deep convolutional neural fields for depth estimation from a single image , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Lei Zhang,et al. Unsupervised Learning-Based Depth Estimation-Aided Visual SLAM Approach , 2020, Circuits Syst. Signal Process..
[40] Roberto Cipolla,et al. Multiview Photometric Stereo , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[41] Liang Lin,et al. Single View Stereo Matching , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[42] Shunli Zhang,et al. Monocular depth estimation with guidance of surface normal map , 2017, Neurocomputing.
[43] Ruigang Yang,et al. Reliability Fusion of Time-of-Flight Depth and Stereo Geometry for High Quality Depth Maps , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[44] Haitao Zhao,et al. Attention-based context aggregation network for monocular depth estimation , 2019, International Journal of Machine Learning and Cybernetics.
[45] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[46] J. M. M. Montiel,et al. ORB-SLAM: A Versatile and Accurate Monocular SLAM System , 2015, IEEE Transactions on Robotics.
[47] Yuan Gao,et al. Symmetric Non-rigid Structure from Motion for Category-Specific Object Structure Estimation , 2016, ECCV.
[48] Gustavo Carneiro,et al. Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue , 2016, ECCV.
[49] Thomas Brox,et al. FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[50] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.