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UNSUPERVISED LEARNING OF IMAGE DEPTH AND EGO-MOTION PREDICTION NEURAL NETWORKS

机译:图像深度和自我预测神经网络的未经监督的学习

摘要

A system includes a neural network implemented by one or more computers, in which the neural network includes an image depth prediction neural network and a camera motion estimation neural network. The neural network is configured to receive a sequence of images. The neural network is configured to process each image in the sequence of images using the image depth prediction neural network to generate, for each image, a respective depth output that characterizes a depth of the image, and to process a subset of images in the sequence of images using the camera motion estimation neural network to generate a camera motion output that characterizes the motion of a camera between the images in the subset. The image depth prediction neural network and the camera motion estimation neural network have been jointly trained using an unsupervised learning technique.
机译:一种系统,包括由一个或多个计算机实现的神经网络,其中,该神经网络包括图像深度预测神经网络和相机运动估计神经网络。神经网络被配置为接收图像序列。神经网络被配置为使用图像深度预测神经网络来处理图像序列中的每个图像,以针对每个图像生成表征图像深度的相应深度输出,并处理序列中的图像子集使用相机运动估计神经网络生成图像的相机运动输出,该输出表征了相机在子集中图像之间的运动。图像深度预测神经网络和相机运动估计神经网络已使用无监督学习技术进行了联合训练。

著录项

  • 公开/公告号EP3688718A1

    专利类型

  • 公开/公告日2020-08-05

    原文格式PDF

  • 申请/专利权人 GOOGLE LLC;

    申请/专利号EP20180812573

  • 申请日2018-11-15

  • 分类号G06T7/20;G06T7/579;

  • 国家 EP

  • 入库时间 2022-08-21 11:38:48

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