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DPointNet: A Density-Oriented PointNet for 3D Object Detection in Point Clouds

arXiv 2102.03747 ↗First posted 7 Feb 2021cs.CVcited by 0

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Abstract (arXiv)

For current object detectors, the scale of the receptive field of feature extraction operators usually increases layer by layer. Those operators are called scale-oriented operators in this paper, such as the convolution layer in CNN, and the set abstraction layer in PointNet++. The scale-oriented operators are appropriate for 2D images with multi-scale objects, but not natural for 3D point clouds with multi-density but scale-invariant objects. In this paper, we put forward a novel density-oriented PointNet (DPointNet) for 3D object detection in point clouds, in which the density of points increases layer by layer. In experiments for object detection, the DPointNet is applied to PointRCNN, and the results show that the model with the new operator can achieve better performance and higher speed than the baseline PointRCNN, which verify the effectiveness of the proposed DPointNet.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 16 of its 26 references that are in the map. First posted on arXiv 7 Feb 2021.

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16 of 26 references.

References · 16

  1. 2016Feature Pyramid Networks for Object Detectioncited by 5,036
  2. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
  3. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,715
  4. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
  5. 2018PointRCNN: 3D Object Proposal Generation and Detection from Point Cloudcited by 941
  6. 2019PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detectioncited by 891
  7. 2017Frustum PointNets for 3D Object Detection from RGB-D Datacited by 640
  8. 20203DSSD: Point-based 3D Single Stage Object Detectorcited by 440
  9. 2019PIXOR: Real-time 3D Object Detection from Point Cloudscited by 358
  10. 2019STD: Sparse-to-Dense 3D Object Detector for Point Cloudcited by 282
  11. 2019Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detectioncited by 124
  12. 2020CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloudcited by 107
4 more
  1. 2020SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloudcited by 16
  2. 2019Range Adaptation for 3D Object Detection in LiDARcited by 8
  3. 20203D Object Detection From LiDAR Data Using Distance Dependent Feature Extractioncited by 1
  4. 2020A Density-Aware PointRCNN for 3D Object Detection in Point Cloudscited by 1

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