3D Recognition: State of the Art and Trends

被引:1
作者
Orlova, S. R. [1 ]
Lopata, A. V. [2 ]
机构
[1] Peter Great St Petersburg Polytech Univ, St Petersburg 195251, Russia
[2] Cent Res & Dev Inst Robot & Tech Cybernet, St Petersburg 194064, Russia
基金
俄罗斯基础研究基金会;
关键词
3D recognition; deep learning; computer vision; NETWORK; CLASSIFICATION;
D O I
10.1134/S0005117922040014
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We consider the field of three-dimensional technical vision and in particular three-dimensional recognition. The problems of three-dimensional vision are singled out, and methods for obtaining and presenting three-dimensional data, as well as applications of three-dimensional vision, are reviewed. Deep learning methods in 3D recognition problems are surveyed. The main modern trends in this field are revealed. So far, quite a few neural network architectures, convolutional layers, sampling, pooling, and aggregation operations, and methods for representing and processing three-dimensional input data have been proposed. The field is under active development, with the greatest variety of methods being presented for point clouds.
引用
收藏
页码:503 / 519
页数:17
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