基于改进Frustum PointNet的3D目标检测 下载: 910次
刘训华, 孙韶媛, 顾立鹏, 李想. 基于改进Frustum PointNet的3D目标检测[J]. 激光与光电子学进展, 2020, 57(20): 201508.
Xunhua Liu, Shaoyuan Sun, Lipeng Gu, Xiang Li. 3D Object Detection Based on Improved Frustum PointNet[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201508.
[1] 张银, 任国全, 程子阳, 等. 三维激光雷达在无人车环境感知中的应用研究[J]. 激光与光电子学进展, 2019, 56(13): 130001.
[2] 刘凯宝, 杨晓红, 何婷婷, 等. InP基近红外单光子雪崩光电探测器阵列[J]. 激光与光电子学进展, 2019, 56(22): 220001.
[3] 季一木, 陈治宇, 田鹏浩, 等. 无人驾驶中3D目标检测方法研究综述[J]. 南京邮电大学学报(自然科学版), 2019, 39(4): 72-79.
[4] Chen XZ, Ma HM, WanJ, et al. Multi-view 3D object detection network for autonomous driving[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 6526- 6534.
[5] Qi CR, LiuW, Wu CX, et al. Frustum PointNets for 3D object detection from RGB-D data[C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 2018: 918- 927.
[6] He K M, Gkioxari G, Dollar P, et al. Mask R-CNN[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, 42(2): 386-397.
[7] Qi CR, YiL, SuH, et al. ( 2017-07-07)[2019-12-23]. https:∥arxiv.org/abs/1706. 02413.
[8] 万鹏. 基于F-PointNet的3D点云数据目标检测[J]. 山东大学学报(工学版), 2019, 49(5): 98-104.
Wan P. Object detection of 3D point clouds based on F-PointNet[J]. Journal of Shandong University (Engineering Science), 2019, 49(5): 98-104.
[9] WooS, ParkJ, Lee JY, et al. CBAM: convolutional block attention module[M] ∥Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science. Cham: Springer, 2018, 11211: 3- 19.
[10] Lin T Y, Goyal P, Girshick R, et al. Focal loss for dense object detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, 42(2): 318-327.
[11] Lin TY, DollárP, GirshickR, et al. Feature pyramid networks for object detection[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 936- 944.
[12] JaderbergM, SimonyanK, ZissermanA, et al. ( 2016-02-04)[2019-12-23]. https:∥arxiv.org/abs/1506. 02025.
[13] GeigerA, LenzP, UrtasunR. Are we ready for autonomous driving? The KITTI vision benchmark suite[C]∥2012 IEEE Conference on Computer Vision and Pattern Recognition, June 16-21, 2012, Providence, RI, USA. New York: IEEE, 2012: 3354- 3361.
[14] LiangM, YangB, Wang SL, 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. Cham: Springer, 2018, 11220: 663- 678.
[15] DengJ, CzarneckiK. MLOD: a multi-view 3D object detection based on robust feature fusion method[C]∥2019 IEEE Intelligent Transportation Systems Conference (ITSC), October 27-30, 2019, Auckland, New Zealand. New York: IEEE, 2019: 279- 284.
刘训华, 孙韶媛, 顾立鹏, 李想. 基于改进Frustum PointNet的3D目标检测[J]. 激光与光电子学进展, 2020, 57(20): 201508. Xunhua Liu, Shaoyuan Sun, Lipeng Gu, Xiang Li. 3D Object Detection Based on Improved Frustum PointNet[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201508.