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3D目标检测综述 阅读笔记

贾添植2021-10-08 19:59点云20

Two Stage

    Multi-View 3D Object Detection Network for Autonomous Driving (CVPR2017)
    RT3D: Real-Time 3-D Vehicle Detection in LiDAR Point Cloud for Autonomous Driving
    Frustum PointNets for 3D Object Detection from RGB-D Data (CVPR2018)
    Joint 3D Proposal Generation and Object Detection from View Aggregation (IROS2018)
    PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud (CVPR2019)
    VoteNet:Deep Hough Voting for 3D Object Detection in Point Clouds
    Multi-Task Multi-Sensor Fusion for 3D Object Detection
    GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving
    Stereo R-CNN based 3D Object Detection for Autonomous Driving
    STD: Sparse-to-Dense 3D Object Detector for Point Cloud
    Part-A^2 Net: 3D Part-Aware and Aggregation Neural Network for Object Detection from Point Cloud
    Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection
    BirdNet: a 3D Object Detection Framework from LiDAR Information(2018 ITSC)
    StarNet: Targeted Computation for Object Detection in Point Clouds
    PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

One Stage

    3D Fully Convolutional Network for Vehicle Detection in Point Cloud (IROS2017)
    Complex-YOLO: An Euler-Region-Proposal for Real-time 3D Object Detection on Point Clouds(ECCV2018)
    YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud(ECCV2018)
    PIXOR: Real-time 3D Object Detection from Point Clouds (CVPR2018)
    HDNET: Exploiting HD Maps for 3D Object Detection (CoRL2018)
    Voxel-FPN: multi-scale voxel feature aggregation in 3D object detection from point clouds
    VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection (CVPR2018)
    LaserNet: An Effcient Probabilistic 3D Object Detector for Autonomous Driving Gregory (Arxiv2019)
    3DSSD: Point-based 3D Single Stage Object Detector


详细解读网上有很多,不一一列出。

未完待续。

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