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

02/07/2021
by   Jie Li, et al.
0

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.

READ FULL TEXT

page 1

page 3

page 4

research
09/11/2020

A Density-Aware PointRCNN for 3D Objection Detection in Point Clouds

We present an improved version of PointRCNN for 3D object detection, in ...
research
12/10/2019

Pillar in Pillar: Multi-Scale and Dynamic Feature Extraction for 3D Object Detection in Point Clouds

Sparsity and varied density are two of the main obstacles for 3D detecti...
research
04/06/2020

SSN: Shape Signature Networks for Multi-class Object Detection from Point Clouds

Multi-class 3D object detection aims to localize and classify objects of...
research
09/06/2021

Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection

We present a flexible and high-performance framework, named Pyramid R-CN...
research
02/10/2020

Object condensation: one-stage grid-free multi-object reconstruction in physics detectors, graph and image data

High-energy physics detectors, images, and point clouds share many simil...
research
12/18/2013

Evaluation of Plane Detection with RANSAC According to Density of 3D Point Clouds

We have implemented a method that detects planar regions from 3D scan da...
research
10/21/2021

A Fast Location Algorithm for Very Sparse Point Clouds Based on Object Detection

Limited by the performance factor, it is arduous to recognize target obj...

Please sign up or login with your details

Forgot password? Click here to reset