Google Inc.

Hossam Isack

Sofien Bouaziz

Shahram Izadi

Aveek Ravishekhar Purohit

Adarsh Prakash Murthy Kowdle

Cem Keskin

Sameh Khamis

Christian Haene

Abhishek Kar

Dmitry Medvedev

According to an aspect, a method for depth estimation includes receiving image data from a sensor system, generating, by a neural network, a first depth map based on the image data, where the first depth map has a first scale, obtaining depth estimates associated with the image data, and transforming the first depth map to a second depth map using the depth estimates, where the second depth map has a second scale.

Depth estimation using a neural network

According to an aspect, a method for pose estimation using a convolutional neural network includes extracting features from an image, downsampling the features to a lower resolution, arranging the features into sets of features, where each set of features corresponds to a separate keypoint of a pose of a subject, updating, by at least one convolutional block, each set of features based on features of one or more neighboring keypoints using a kinematic structure, and predicting the pose of the subject using the updated sets of features.

Human pose estimation using neural networks and kinematic structure

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Mountain View, CA, United States of America

Hossam Isack