Optical Technique, Volume. 50, Issue 6, 713(2024)

Research on Pseudo-LiDAR improvement algorithm for 3D object detection based on Gaussian filtering for stereo cameras

LI Yanming, SU Jianqiang*, LIU Peng, and ZHANG Lijie
Author Affiliations
  • Institute of Electric Power, Inner Mongolia University of Technology, Huhhot 010051, China
  • show less
    References(18)

    [1] [1] Chen X, Kundu K, Zhang Z, et al. Monocular 3d object detection for autonomous driving[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV, USA:IEEE.2016:2147—2156.

    [5] [5] Chen X, Kundu K, Zhu Y, et al. 3d object proposals using stereo imagery for accurate object class detection[J]. IEEE transactions on pattern analysis and machine intelligence,2017,40(5):1259—1272.

    [6] [6] Ji C F, Liu G Z, Zhao D. Stereo 3D object detection via instance depth prior guidance and adaptive spatial feature aggregation[J]. Visual Computer,2023,39(10):4543—54.

    [7] [7] Gao A, Pang Y, Nie J, et al. ESGN: Efficient stereo geometry network for fast 3D object detection[J]. IEEE Transactions on Circuits and Systems for Video Technology,2022,34(4):2000—2009.

    [11] [11] Chen X, Kundu K, Zhu Y, et al. 3d object proposals using stereo imagery for accurate object class detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2017,40(5):1259—1272.

    [12] [12] Girshick R. Fast r-cnn[C]∥2015 IEEE International Conference on Computer Vision (ICCV). Santiago, Chile:IEEE,2015:1440—1448.

    [13] [13] Li P, Chen X, Shen S. Stereo r-cnn based 3d object detection for autonomous driving[C]∥2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Long Beach, CA, USA:IEEE,2019:7644—7652.

    [14] [14] 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]∥2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Long Beach, CA, USA:IEEE,2019:8445—8453.

    [15] [15] Chang J R, Chen Y S. Pyramid stereo matching network[C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City, UT, USA:IEEE,2018:5410—5418.

    [16] [16] Shi S, Guo C, Jiang L, et al. Pv-rcnn: Point-voxel feature set abstraction for 3d object detection[C]∥2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Seattle, WA, USA:IEEE,2020:10529—10538.

    [17] [17] Ku J, Mozifian M, Lee J, et al. Joint 3d proposal generation and object detection from view aggregation[C]∥2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain:IEEE,2018:1—8.

    [18] [18] Wang C Y, Bochkovskiy A, Liao H Y M. YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors[C]∥2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Vancouver, BC, Canada:IEEE,2023:7464—7475.

    [19] [19] Chen Y, Liu S, Shen X, et al. Dsgn: Deep stereo geometry network for 3d object detection[C]∥2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Seattle, WA, USA:IEEE,2020:12536—12545.

    [20] [20] Sun J, Chen L, Xie Y, et al. Disp r-cnn: Stereo 3d object detection via shape prior guided instance disparity estimation[C]∥2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR).Seattle,WA,USA:IEEE,2020:10548—10557.

    [21] [21] Garg D, Wang Y, Hariharan B, et al. Wasserstein distances for stereo disparity estimation[C]∥Advances in Neural Information Processing Systems, Cambridge,MIT Press,2020:22517—22529.

    [22] [22] Ji C F, Liu G Z, Zhao D. Stereo 3D object detection via instance depth prior guidance and adaptive spatial feature aggregation[J]. Visual Computer,2023,39(10):4543—54.

    [23] [23] Liu Y, Wang L, Liu M. Yolostereo3d: A step back to 2d for efficient stereo 3d detection[C]∥2021 IEEE International Conference on Robotics and Automation (ICRA). Xi’an, China:IEEE,2021:13018—13024.

    [24] [24] Shi Y, Guo Y, Mi Z, et al. Stereo CenterNet-based 3D object detection for autonomous driving[J]. Neurocomputing,2022,471:219—229.

    Tools

    Get Citation

    Copy Citation Text

    LI Yanming, SU Jianqiang, LIU Peng, ZHANG Lijie. Research on Pseudo-LiDAR improvement algorithm for 3D object detection based on Gaussian filtering for stereo cameras[J]. Optical Technique, 2024, 50(6): 713

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Dec. 18, 2023

    Accepted: Jan. 21, 2025

    Published Online: Jan. 21, 2025

    The Author Email: Jianqiang SU (sujianqiang1983@163.com)

    DOI:

    Topics