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Employing three-dimensional (3D) data predicted from two-dimensional (2D) images using neural networks for 3D modeling applications and other applications

机译:使用用于3D建模应用程序和其他应用的神经网络从二维(2D)图像中预测的三维(3D)数据预测

摘要

The disclosed subject matter is directed to employing machine learning models configured to predict 3D data from 2D images using deep learning techniques to derive 3D data for the 2D images. In some embodiments, a system is described comprising a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory. The computer executable components comprise a reception component configured to receive two-dimensional images, and a three-dimensional data derivation component configured to employ one or more three-dimensional data from two-dimensional data (3D-from-2D) neural network models to derive three-dimensional data for the two-dimensional images.
机译:所公开的主题涉及采用机器学习模型,该机器学习模型被配置为使用深度学习技术从2D图像预测3D数据,以导出2D图像的3D数据。 在一些实施例中,描述了一种系统,包括存储计算机可执行组件的存储器,以及执行存储在存储器中的计算机可执行组件的处理器。 计算机可执行组件包括被配置为接收二维图像的接收组件,以及配置为使用来自二维数据(3D-2D)神经网络模型的一个或多个三维数据的三维数据推导组件 导出二维图像的三维数据。

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