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JOURNALS // Avtomatika i Telemekhanika // Archive

Avtomat. i Telemekh., 2022 Issue 4, Pages 5–26 (Mi at15772)

Surveys

3D recognition: state of the art and trends

S. R. Orlovaa, A. V. Lopotab

a Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195251 Russia
b Central Research and Development Institute of Robotics and Technical Cybernetics, St. Petersburg, 194064 Russia

Abstract: 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.

Keywords: 3D recognition, deep learning, computer vision.

Presented by the member of Editorial Board: D. V. Vinogradov

Received: 09.08.2021
Revised: 27.12.2021
Accepted: 30.12.2021

DOI: 10.31857/S000523102204002X


 English version:
Automation and Remote Control, 2022, 83:4, 503–519


© Steklov Math. Inst. of RAS, 2026