[1] [1] QI C R,SU H,MO K,et al.Pointnet:deep learning on point sets for 3d classification and segmentation［C］//IEEE Conference on Computer Vision and Pattern Recognition,July 21-26,2017,Honolulu,Hawaii,USA.New York:IEEE,2017:652-660.

[2] [2] QI C R,YI L,SU H,et al.PointNet++:deep hierarchical feature learning on point sets in a metric space[J].Advances in Neural Information Processing Systems,2017,30(3):231-237.

[3] [3] HUANG Q,WANG W,NEUMANN U.Recurrent slice networks for 3d segmentation of point clouds［C］//IEEE Conference on Computer Vision and Pattern Recognition,June 18-23,2018,Salt Lake City,Utah,USA.New York:IEEE,2018:2626-2635.

[4] [4] WANG Y,SUN Y,LIU Z,et al.Dynamic graph CNN for learning on point clouds[J].ACM Transactions on Graphics,2019,38(5):1-12.

[5] [5] LI Y,BU R,SUN M,et al.PointCNN:convolution on x-transformed points[J].Advances in Neural Information Processing Systems,2018,31(2):820-830.

[6] [6] LIU X,CHEN Y,LI S,et al.Hierarchical classification of urban ALS data by using geometry and intensity information[J].Sensors,2019,19(20):4583-4588.

[7] [7] NIKHIL G N,MERAZ M,JAVED M.Automatic on-road object detection in lidar-point cloud data using modified voxelnet architecture［C］//International Conference on Computer Vision and Image Processing,December 4-6,2020,Prayagraj,India.Singspore:Springer,2020:201-213.

[8] [8] MUNOZ D,BAGNELL J A,VANDAPEL N,et al.Contextual classification with functional Max-Margin Markov Networks［C］//Computer Vision and Pattern Recognition,June 20-25,2009,Miami,Florida,USA.New York:IEEE,2009:975-982.

[9] [9] HU H,MUNOZ D,BAGNELL J A,et al.Efficient 3D scene analysis from streaming data［C］//International Conference on Robotics and Automation,May 6-10,2013,Karlsruhe,Germany.New York:IEEE,2013:2297-2304.

[10] [10] GEVAERT C M,PERSELLO C,VOSSELMAN G.Optimizing multiple kernel learning for the classification of UAV data[J].Remote Sensing,2016,8(2):1025-1039.

[11] [11] WEST K F,WEBB B N,LERSCH J R,et al.Context-driven automated target detection in 3D data［C］//Automatic Target Recognition XIV,April 13-15,2004,Oriando,Florida,USA.Bellingham:SPIE,2004:133-143.

[12] [12] WOLF D,PRANKL J,VINCZE M.Fast semantic segmentation of 3D point clouds using a dense CRF with learned parameters［C］//IEEE International Conference on Robotics and Automation,May 26-30,2015,Washington,USA.New York:IEEE,2015:4867-4873.

[13] [13] MALLET C,BRETAR F,ROUX M,et al.Relevance assessment of full-waveform lidar data for urban area classification[J].ISPRS Journal of Photogrammetry and Remote Sensing,2011,66(6):71-84.

[14] [14] WEINMANN M,JUTZI B,HINZ S,et al.Semantic point cloud interpretation based on optimal neighborhoods,relevant features and efficient classifiers[J].ISPRS Journal of Photogrammetry and Remote Sensing,2015,105(105):286-304.

[15] [15] LIU Z,WU B,LUO W,et al.Bi-real Net:enhancing the performance of 1-bit cnns with improved representational capability and advanced training algorithm［C］//European Conference on Computer Vision,September 8-14,2018,Munich,Germany.Berlin:Springer,2018:722-737.

[16] [16] MARTINEZ B,YANG J,BULAT A,et al.Training binary neural networks with real-to-binary convolutions［C］//International Conference on Learning Representations,April 26-May 1,2020,Addis Ababa,Ethiopia.Berlin:Springer,2020:11535-11541.

[17] [17] RASTEGARI M,ORDONEZ V,REDMON J,et al.XNOR-Net:imagenet classification using binary convolutional neural networks［C］//European Conference on Computer Vision,October 11-14,2016,Amsterdam,The Netherlands.Berlin:Springer,2016:525-542.

[18] [18] QIN H,GONG R,LIU X,et al.Forward and backward Information retention for accurate binary neural networks［C］//Computer Vision and Pattern Recognition,June 13-19,2020,Seattle,Washington,USA.New York:IEEE,2020:2250-2259.

[19] [19] CHEN Y,DAI X,LIU M,et al.Dynamic relu［C］//European Conference on Computer Vision,August 23-28,2020,Glasgow,US.Berlin:Springer,2020:351-367.

[21] [21] WANG L,MENG W,XI R,et al.Large-scale 3D point cloud classification based on feature description matrix by CNN［C］//Computer Animation and Social Agents,May 21-23,2018,Beijing,China.Berlin:Springer,2018:43-47.

[22] [22] MUNOZ D,VANDAPEL N,HEBERT M.Directional associative markov network for 3D point cloud classification[J].International Symposium on 3-D Data Processing,Visualization,and Transmission,2008,4(2):23-31.

[23] [23] BLOMLEY R,WEINMANN M.Using multi-scale features for the 3D semantic labeling of airborne laser scanning data[J].ISPRS Annals of Photogrammetry,Remote Sensing & Spatial Information Sciences,2017,4(3):15-21.

[24] [24] Li H,Meng W,Liu X,et al.Parameter optimization criteria guided 3D point cloud classification[J].Multimedia Tools and Applications,2019,78(4):5081-5104.