3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-Scale 3D Point Clouds
暂无分享,去创建一个
Jiwen Lu | Chenghu Zhou | Liqiang Zhang | Fangyu Liu | Shuaipeng Li | Yuebin Wang | Rongtian Ye | Jiwen Lu | Chenghu Zhou | Yuebin Wang | Shuaipeng Li | Liqiang Zhang | Rongtian Ye | Fangyu Liu
[1] Vladlen Koltun,et al. Multi-Scale Context Aggregation by Dilated Convolutions , 2015, ICLR.
[2] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[3] Thorsten Joachims,et al. Semantic Labeling of 3D Point Clouds for Indoor Scenes , 2011, NIPS.
[4] Zhen Wang,et al. A Multiscale and Hierarchical Feature Extraction Method for Terrestrial Laser Scanning Point Cloud Classification , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[5] Iasonas Kokkinos,et al. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs , 2014, ICLR.
[6] Silvio Savarese,et al. 3D Semantic Parsing of Large-Scale Indoor Spaces , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[7] Ross B. Girshick,et al. Fast R-CNN , 2015, 1504.08083.
[8] Zhen Wang,et al. A Multilevel Point-Cluster-Based Discriminative Feature for ALS Point Cloud Classification , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[9] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[10] Mikkel Kragh Hansen,et al. Object Detection and Terrain Classification in Agricultural Fields Using 3D Lidar Data , 2015, ICVS.
[11] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[12] Jianxiong Xiao,et al. Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[14] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[15] Thomas A. Funkhouser,et al. Semantic Scene Completion from a Single Depth Image , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Bisheng Yang,et al. Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data , 2017 .
[17] Florent Lafarge,et al. Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation , 2012, International Journal of Computer Vision.
[18] Alex Graves,et al. Playing Atari with Deep Reinforcement Learning , 2013, ArXiv.
[19] S. Savarese,et al. Semantic Parsing of Large-Scale Indoor Spaces , 2016 .
[20] Liangpei Zhang,et al. Tensor Discriminative Locality Alignment for Hyperspectral Image Spectral–Spatial Feature Extraction , 2013, IEEE Transactions on Geoscience and Remote Sensing.
[21] C. Mallet,et al. AIRBORNE LIDAR FEATURE SELECTION FOR URBAN CLASSIFICATION USING RANDOM FORESTS , 2009 .
[22] Sebastian Scherer,et al. 3D Convolutional Neural Networks for landing zone detection from LiDAR , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[23] Liangpei Zhang,et al. A pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[24] Jianxiong Xiao,et al. Sliding Shapes for 3D Object Detection in Depth Images , 2014, ECCV.
[25] Thomas Serre,et al. Object recognition with features inspired by visual cortex , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[26] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Jianxiong Xiao,et al. 3D ShapeNets: A deep representation for volumetric shapes , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[29] Kunihiko Fukushima,et al. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.
[30] Luc Van Gool,et al. 3D all the way: Semantic segmentation of urban scenes from start to end in 3D , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[31] P. Cochat,et al. Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.
[32] Leonidas J. Guibas,et al. Volumetric and Multi-view CNNs for Object Classification on 3D Data , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Qi Zhang,et al. Deep learning-based tree classification using mobile LiDAR data , 2015 .
[34] Sebastian Scherer,et al. VoxNet: A 3D Convolutional Neural Network for real-time object recognition , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[35] Andrew E. Johnson,et al. Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999, IEEE Trans. Pattern Anal. Mach. Intell..
[36] Ulrich Neumann,et al. Complete residential urban area reconstruction from dense aerial LiDAR point clouds , 2013, Graph. Model..
[37] Leonidas J. Guibas,et al. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).