Microsoft Technology Licensing, LLC

Mandar Dilip Dixit

Gang Hua

Bo Liu

A neural network architecture for attention-based efficient model adaptation is disclosed. A method includes accessing an input vector, the input vector comprising a numeric representation of an input to a neural network. The method includes providing the input vector to the neural network comprising a plurality of ordered layers, wherein each layer in at least a subset of the plurality of ordered layers is coupled with an adaptation module, wherein the adaptation module receives a same input value as a coupled layer for the adaptation module, and wherein an output value of the adaptation module is pointwise multiplied with an output value of the coupled layer to generate a next layer input value. The method includes generating an output of the neural network based on an output of a last one of the plurality of ordered layers in the neural network.

Neural network architecture for attention based efficient model adaptation

Examples are disclosed that relate to computing devices and methods for synthesizing a novel pose of an object. One example provides a method comprising receiving a reference image of an object corresponding to an original viewpoint. The reference image of the object is translated into a depth map of the object, and a new depth map of the object is synthesized to correspond to a new viewpoint. A new image of the object is generated from the new viewpoint based on the new depth map of the object and the reference image of the object.

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Redond, WA, United States of America

Mandar Dilip Dixit