Systems and methods for machine learned image conversion
AssigneeNintendo Co., Ltd.
InventorsAlexandre DELATTRE, Théo CHARVET, Raphaël PONCET
Life of this patent
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Abstract
A computer system is provided for converting images through use of a trained neural network. A source image is divided into blocks and context data is added to each pixel block. The context blocks are split into channels and each channel from the same context block is added to the same activation matrix. The action matrix is then executed against a trained neural network to produce a changed activation matrix. The changed activation matrix is then used to generate a converted image.
Claims21
(canceled)
A non-transitory computer readable storage medium storing computer executable instructions for use with a computing system, the stored instructions configured to perform operations comprising:
- accessing a plurality of images that include a first image in the first resolution;
- dividing the first image into a first plurality of pixel blocks;
- splitting each one of the first plurality of pixel blocks into a plurality of separate output channels to form target output data;
- generating, based on one of the plurality of separate output channels, data for a second image that is of the second resolution;
- generating, from the data for the second image, a plurality of context blocks;
- splitting the plurality of context blocks into a plurality of separate input channels to form input data;
- and
- training a neural network by using the input data until convergence of the neural network to the target output data.
A method of training a neural network to transform images, the method comprising:
- accessing a plurality of images that include a first image in the first resolution;
- dividing the first image into a first plurality of pixel blocks;
- splitting each one of the first plurality of pixel blocks into a plurality of separate output channels to form target output data;
- generating, based on one of the plurality of separate output channels, data for a second image that is of the second resolution;
- generating, from the data for the second image, a plurality of context blocks;
- splitting the plurality of context blocks into a plurality of separate input channels to form input data;
- and
- training a neural network by using the input data until convergence of the neural network to the target output data.
A computer system for training a neural network, the computer system comprising:
- a processing system that includes at least one hardware processor configured to perform operations comprising:
- accessing a plurality of images that include a first image in the first resolution;
- and
- dividing the first image into a first plurality of pixel blocks,
- splitting each one of the first plurality of pixel blocks into a plurality of separate output channels to form target output data,
- generating, based on one of the plurality of separate output channels, data for a second image that is of the second resolution,
- generating, from the data for the second image, a plurality of context blocks,
- splitting the plurality of context blocks into a plurality of separate input channels to form input data, and
- training a neural network by using the input data until convergence of the neural network to the target output data.
Dependencies are inferred from the claim text.