南京大学学报（自然科学版）2023，Vol.59Issue(6)：996-1002,7.DOI:10.13232/j.cnki.jnju.2023.06.009
基于俯视角融合的多模态三维目标检测
Multi-modal 3D object detection based on Bird-Eye-View fusion
摘要
Abstract
In order to solve the problem that it is difficult to obtain target distance information from image data and target category information from point cloud data in 3D object detection,a method is proposed to convert the image into Bird-Eye-View features.This method flattens the multi-scale image features according to horizontal dimensions and transforms them into multi-scale image Bird-Eye-View features through dense transformation layers,and finally reshapes them into global image top angle features.On this basis,a multi-modal 3D object detection network based on Bird-Eye-View fusion is proposed to fuse the Bird-Eye-View features of image and point cloud with feature concating or element addition.Experiments on KITTI data set show that the multi-modal 3D object detection network based on Bird-Eye-View fusion proposed in this paper is better than other popular 3D object detection methods for vehicles and pedestrians.关键词
三维目标检测/多模态融合/点云/俯视角/深度学习Key words
3D object detection/multi-modal fusion/point cloud/Bird-Eye-View/deep learning分类
交通工程引用本文复制引用
钱多,殷俊..基于俯视角融合的多模态三维目标检测[J].南京大学学报（自然科学版）,2023,59(6):996-1002,7.基金项目
上海市浦江人才计划(22PJD029) （22PJD029）
