Sparsity Invariant CNNs
暂无分享,去创建一个
Thomas Brox | Nick Schneider | Andreas Geiger | Jonas Uhrig | Lukas Schneider | Uwe Franke | T. Brox | Andreas Geiger | U. Franke | J. Uhrig | N. Schneider | Lukas Schneider
[1] Ben Graham,et al. Sparse 3D convolutional neural networks , 2015, BMVC.
[2] Carsten Rother,et al. Depth Super Resolution by Rigid Body Self-Similarity in 3D , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[3] Thomas Brox,et al. A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Michael S. Brown,et al. High quality depth map upsampling for 3D-TOF cameras , 2011, 2011 International Conference on Computer Vision.
[5] Xiaoou Tang,et al. Depth Map Super-Resolution by Deep Multi-Scale Guidance , 2016, ECCV.
[6] Sebastian Thrun,et al. An Application of Markov Random Fields to Range Sensing , 2005, NIPS.
[7] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] Rob Fergus,et al. Depth Map Prediction from a Single Image using a Multi-Scale Deep Network , 2014, NIPS.
[9] Yiran Chen,et al. Learning Structured Sparsity in Deep Neural Networks , 2016, NIPS.
[10] Xueying Qin,et al. Deep Depth Super-Resolution: Learning Depth Super-Resolution Using Deep Convolutional Neural Network , 2016, ACCV.
[11] Heiko Hirschmüller,et al. Stereo Processing by Semiglobal Matching and Mutual Information , 2008, IEEE Trans. Pattern Anal. Mach. Intell..
[12] Marc Pollefeys,et al. Semantically Guided Depth Upsampling , 2016, GCPR.
[13] Ruigang Yang,et al. Spatial-Depth Super Resolution for Range Images , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[14] Simon Haykin,et al. GradientBased Learning Applied to Document Recognition , 2001 .
[15] Klaus Diepold,et al. Dense disparity maps from sparse disparity measurements , 2011, 2011 International Conference on Computer Vision.
[16] Yiran Chen,et al. Holistic SparseCNN: Forging the Trident of Accuracy, Speed, and Size , 2016, ArXiv.
[17] Ming-Yu Liu,et al. Joint Geodesic Upsampling of Depth Images , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[18] E. Nadaraya. On Estimating Regression , 1964 .
[19] Ji Wan,et al. Multi-view 3D Object Detection Network for Autonomous Driving , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Qiang Qiu,et al. Oriented Response Networks , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[21] F. Michael,et al. PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions , 2016, ICLR 2016.
[22] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Max Welling,et al. Group Equivariant Convolutional Networks , 2016, ICML.
[24] Joachim M. Buhmann,et al. TI-POOLING: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[26] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[27] 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.
[28] Kyoung Mu Lee,et al. Accurate Image Super-Resolution Using Very Deep Convolutional Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Hassan Foroosh,et al. Sparse Convolutional Neural Networks , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Xiaoou Tang,et al. Learning a Deep Convolutional Network for Image Super-Resolution , 2014, ECCV.
[31] G. S. Watson,et al. Smooth regression analysis , 1964 .
[32] Lior Wolf,et al. InterpoNet, a Brain Inspired Neural Network for Optical Flow Dense Interpolation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Michal Irani,et al. Super-resolution from a single image , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[35] Song Han,et al. Learning both Weights and Connections for Efficient Neural Network , 2015, NIPS.
[36] Gernot Riegler,et al. OctNet: Learning Deep 3D Representations at High Resolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[37] Sebastian Ramos,et al. The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[38] Xi Wang,et al. High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth , 2014, GCPR.
[39] Horst Bischof,et al. Image Guided Depth Upsampling Using Anisotropic Total Generalized Variation , 2013, 2013 IEEE International Conference on Computer Vision.
[40] Dani Lischinski,et al. Joint bilateral upsampling , 2007, SIGGRAPH 2007.
[41] Xiaoou Tang,et al. Image Super-Resolution Using Deep Convolutional Networks , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[42] Jianxiong Xiao,et al. SUN RGB-D: A RGB-D scene understanding benchmark suite , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[43] Bernhard Schölkopf,et al. Mask-Specific Inpainting with Deep Neural Networks , 2014, GCPR.
[44] Qiao Wang,et al. VirtualWorlds as Proxy for Multi-object Tracking Analysis , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[45] Daniel Cremers,et al. FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture , 2016, ACCV.
[46] Gabriel J. Brostow,et al. Patch Based Synthesis for Single Depth Image Super-Resolution , 2012, ECCV.
[47] Jonathan T. Barron,et al. The Fast Bilateral Solver , 2015, ECCV.
[48] Horst Bischof,et al. ATGV-Net: Accurate Depth Super-Resolution , 2016, ECCV.
[49] Benjamin Graham,et al. Spatially-sparse convolutional neural networks , 2014, ArXiv.
[50] Horst Bischof,et al. A Deep Primal-Dual Network for Guided Depth Super-Resolution , 2016, BMVC.
[51] Thomas S. Huang,et al. Image Super-Resolution Via Sparse Representation , 2010, IEEE Transactions on Image Processing.
[52] Ian D. Reid,et al. Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[53] Peter V. Gehler,et al. Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[54] Andreas Geiger,et al. Object scene flow for autonomous vehicles , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[55] Andrea Vedaldi,et al. Warped Convolutions: Efficient Invariance to Spatial Transformations , 2016, ICML.
[56] Andrew Zisserman,et al. Spatial Transformer Networks , 2015, NIPS.
[57] Antonio M. López,et al. The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[58] Patrice Y. Simard,et al. Best practices for convolutional neural networks applied to visual document analysis , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..
[59] Thomas Brox,et al. DeMoN: Depth and Motion Network for Learning Monocular Stereo , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[60] Sebastian Thrun,et al. Upsampling range data in dynamic environments , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[61] Richard Szeliski,et al. A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.
[62] Sebastian Thrun,et al. A Noise‐aware Filter for Real‐time Depth Upsampling , 2008 .
[63] Andreas Geiger,et al. Vision meets robotics: The KITTI dataset , 2013, Int. J. Robotics Res..
[64] Tian Xia,et al. Vehicle Detection from 3D Lidar Using Fully Convolutional Network , 2016, Robotics: Science and Systems.
[65] Stephan J. Garbin,et al. Harmonic Networks: Deep Translation and Rotation Equivariance , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[66] 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).