3D recognition: state of the art and trends

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.