[1] Geiger A, Lenz P, Urtasun R. Are we ready for autonomous driving? The KITTI vision benchmark suite[C], 3354-3361(2012).

[2] Gomez-Ojeda R, Briales J, Gonzalez-Jimenez J. PL-SVO: semi-direct monocular visual odometry by combining points and line segments[C], 4211-4216(2016).

[3] Park Y, Lepetit V, Woo W. Multiple 3D object tracking for augmented reality[C], 117-120(2008).

[4] Baltrušaitis T, Ahuja C, Morency L P. Multimodal machine learning: a survey and taxonomy[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41, 423-443(2019).

[5] Xie L, Xiang C, Yu Z X et al. PI-RCNN: an efficient multi-sensor 3D object detector with point-based attentive cont-conv fusion module[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 12460-12467(2020).

[6] Chen X Z, Ma H M, Wan J et al. Multi-view 3D object detection network for autonomous driving[C], 6526-6534(2017).

[7] Mousavian A, Anguelov D, Flynn J et al. 3D bounding box estimation using deep learning and geometry[C], 5632-5640(2017).

[8] Chabot F, Chaouch M, Rabarisoa J et al. Deep MANTA: a coarse-to-fine many-task network for joint 2D and 3D vehicle analysis from monocular image[C], 1827-1836(2017).

[9] Mottaghi R, Xiang Y, Savarese S. A coarse-to-fine model for 3D pose estimation and sub-category recognition[C], 418-426(2015).

[10] Wang Y, Chao W L, Garg D et al. Pseudo-LiDAR from visual depth estimation: bridging the gap in 3D object detection for autonomous driving[C], 8437-8445(2019).

[11] You Y R, Wang Y, Chao W L et al. Pseudo-LiDAR++: accurate depth for 3D object detection in autonomous driving[EB/OL]. https://arxiv.org/abs/1906.06310

[12] Li B Y, Ouyang W L, Sheng L, G et al. S3D: an efficient 3D object detection framework for autonomous driving[C], 1019-1028(2019).

[13] Li P L, Chen X Z, Shen S J. Stereo R-CNN based 3D object detection for autonomous driving[C], 7636-7644(2019).

[14] Zhou Y, Tuzel O. VoxelNet: end-to-end learning for point cloud based 3D object detection[C], 4490-4499(2018).

[15] Yan Y, Mao Y X, Li B. SECOND: sparsely embedded convolutional detection[J]. Sensors, 18, E3337(2018).

[16] Lang A H, Vora S, Caesar H et al. PointPillars: fast encoders for object detection from point clouds[C], 12689-12697(2019).

[17] Charles R Q, Hao S, Mo K C et al. PointNet: deep learning on point sets for 3D classification and segmentation[C], 77-85(2017).

[18] Shi S S, Wang X G, Li H S. PointRCNN: 3D object proposal generation and detection from point cloud[C], 770-779(2019).

[19] Chen Y L, Liu S, Shen X Y et al. Fast point R-CNN[C], 9774-9783(2019).

[20] Yang Z T, Sun Y N, Liu S et al. STD: sparse-to-dense 3D object detector for point cloud[C], 1951-1960(2019).

[21] Shi S S, Guo C X, Jiang L et al. PV-RCNN: point-voxel feature set abstraction for 3D object detection[C], 10526-10535(2020).

[22] Shi S S, Wang Z, Shi J P et al. From points to parts: 3D object detection from point cloud with part-aware and part-aggregation network[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43, 2647-2664(2021).

[23] Qi C R, Liu W, Wu C X et al. Frustum PointNets for 3D object detection from RGB-D data[C], 918-927(2018).

[24] Xu D F, Anguelov D, Jain A. PointFusion: deep sensor fusion for 3D bounding box estimation[C], 244-253(2018).

[25] Wang Z X, Jia K. Frustum ConvNet: sliding frustums to aggregate local point-wise features for amodal 3D object detection[C], 1742-1749(2019).

[26] Chen X Z, Ma H M, Wan J et al. Multi-view 3D object detection network for autonomous driving[C], 6526-6534(2017).

[27] Ku J, Mozifian M, Lee J et al. Joint 3D proposal generation and object detection from view aggregation[C], 18392975(2018).

[28] Liang M, Yang B, Chen Y et al. Multi-task multi-sensor fusion for 3D object detection[C], 7337-7345(2019).

[29] Liang M, Yang B, Wang S L et al. Deep continuous fusion for multi-sensor 3D object detection[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11220, 663-678(2018).

[30] Girshick R. Fast R-CNN[C], 1440-1448(2015).

[31] Chen X Z, Kundu K, Zhang Z Y et al. Monocular 3D object detection for autonomous driving[C], 2147-2156(2016).

[32] Chen X Z, Kundu K, Zhu Y K et al. 3D object proposals using stereo imagery for accurate object class detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 1259-1272(2018).

[33] Li B, Zhang T L, Xia T. Vehicle detection from 3D lidar using fully convolutional network[EB/OL]. https://arxiv.org/abs/1608.07916