Method and apparatus of spatially sparse convolution module for visual rendering and synthesis
AssigneeIntel Corporation
InventorsAnbang Yao, Ming Lu, Yikai Wang, Scott Janus, Sungye Kim
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Abstract
Embodiments are generally directed to methods and apparatuses of spatially sparse convolution module for visual rendering and synthesis. An embodiment of a method for image processing, comprising: receiving an input image by a convolution layer of a neural network to generate a plurality of feature maps; performing spatially sparse convolution on the plurality of feature maps to generate spatially sparse feature maps; and upsampling the spatially sparse feature maps to generate an output image.
Claims20
An apparatus comprising:
- processing circuitry to:
- receive an input image by a convolution layer of a neural network to generate a plurality of feature maps;
- perform spatially sparse convolution on the plurality of feature maps to generate spatially sparse feature maps;
- and
- upsample the spatially sparse feature maps to generate an output image.
A method comprising:
- receiving, by one or more processors, an input image by a convolution layer of a neural network to generate a plurality of feature maps;
- performing spatially sparse convolution on the plurality of feature maps to generate spatially sparse feature maps;
- and
- upsampling the spatially sparse feature maps to generate an output image.
At least one computer-readable medium comprising instructions which, when executed, cause a computing device to perform operations comprising:
- receiving an input image by a convolution layer of a neural network to generate a plurality of feature maps;
- performing spatially sparse convolution on the plurality of feature maps to generate spatially sparse feature maps;
- and
- upsampling the spatially sparse feature maps to generate an output image.
Dependencies are inferred from the claim text.