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US 11,113,800 B2Granted
Filtering image data using a neural network
AssigneeNVIDIA Corporation
InventorsAnton S. Kaplanyan, Chakravarty Reddy Alla Chaitanya, Timo Oskari Aila, Aaron Eliot Lefohn, Marco Salvi
Life of this patent
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Abstract
A method, computer readable medium, and system are disclosed for performing spatiotemporal filtering. The method includes identifying image data to be rendered, reconstructing the image data to create reconstructed image data, utilizing a filter including a neural network having one or more skip connections and one or more recurrent layers, and returning the reconstructed image data.
Claims20
A method for performing spatiotemporal filtering, comprising:
- identifying image data to be rendered, the image data including:
- color data, and
- one or more auxiliary features that include at least one of one or more view-space shading normals, one or more depth values, or one or more roughness values;
- reconstructing the image data to create reconstructed image data, utilizing a filter including a neural network that processes the image data based on the one or more auxiliary features, the neural network having:
- one or more skip connections, and
- one or more recurrent layers that retain, at least in part, the one or more auxiliary features unchanged;
- and
- returning the reconstructed image data and the unchanged one or more auxiliary features.
5 more elements
A system comprising:
- a processor that is configured to:
- identify image data to be rendered, the image data including:
- color data, and
- one or more auxiliary features that include at least one of one or more view-space shading normals, one or more depth values, or one or more roughness values;
- reconstruct the image data to create reconstructed image data, utilizing a filter including a neural network that processes the image data based on the one or more auxiliary features, the neural network having:
- one or more skip connections, and
- one or more recurrent layers that retain, at least in part, the one or more auxiliary features unchanged;
- and
- return the reconstructed image data and the unchanged one or more auxiliary features.
6 more elements
A method for performing spatiotemporal filtering, comprising:
- identifying image data to be rendered, the image data resulting from a Monte Carlo sampling method and the image data including:
- color data, and
- one or more auxiliary features that include at least one of one or more view-space shading normals, one or more depth values, or one or more roughness values;
- applying a filter to the image data to create reconstructed image data, where the filter is a neural network that processes the image data based on the one or more auxiliary features, the neural network having:
- one or more skip connections, and
- one or more recurrent layers that retain, at least in part, the one or more auxiliary features unchanged;
- and
- returning the reconstructed image data and the unchanged one or more auxiliary features.
5 more elements
Dependencies are inferred from the claim text.