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VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
时间 2020-12-30
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3D检测
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VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection 简介 3D目标检测整体框架 特征学习网络 卷积中间层 区域提出网络(RPN) loss 简介 3D点云中物体的精确检测是许多应用中的一个核心问题,为了将高度稀疏的激光雷达点云与区域建议网络(RPN)进行接口。处理LIDAR点云的难点:点云稀疏、点云密度变化
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相关文章
1.
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
2.
VoxelNet:End-to-End Learning for Point Cloud Based 3D Object Detection阅读笔记
3.
3D Object Detection——Voxel based methods
4.
三维目标检测论文阅读:VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
5.
【文章阅读】STD:Sparse-to-Dense 3D Object Detector for Point Cloud
6.
Structure Aware Single-stage 3D Object Detection from Point Cloud
7.
3d fully convolutional network for vehicle detection in point cloud
8.
RepPoints: Point Set Representation for Object Detection
9.
PointPillars: Fast Encoders for 3D Object Detection from Point Clouds
10.
Point Cloud 2019
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