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US 2025/0097474 A1Published application
Adaptive quantization for neural network weights for convolution neural network filters in video coding
AssigneeQUALCOMM Incorporated
InventorsYun Li, Dmytro Rusanovskyy, Marta Karczewicz
Life of this patent
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Abstract
A device for decoding video data is configured to determine first neural network (NN) weights for a layer of a convolutional neural network (CNN) filter; derive a quantization value for the layer of the CNN filter based on values of the first NN weights; convert the first NN weights to second NN weights based on the quantization value; and filter a block of the video data using the second NN weights.
Claims20
A method of decoding video data, the method comprising:
- determining first neural network (NN) weights for a layer of a convolutional neural network (CNN) filter;
- deriving a quantization value for the layer of the CNN filter based on values of the first NN weights;
- converting the first NN weights to second NN weights based on the quantization value;
- filtering a block of the video data using the second NN weights to produce a filtered block of video data;
- and
- outputting a picture of decoded video data that includes the filtered block.
3 more elements
A device for decoding video data, the device comprising:
- a memory configured to store video data;
- one or more processors implemented in circuitry and configured to:
- determine first neural network (NN) weights for a layer of a convolutional neural network (CNN) filter;
- derive a quantization value for the layer of the CNN filter based on values of the first NN weights;
- convert the first NN weights to second NN weights based on the quantization value;
- filter a block of the video data using the second NN weights to produce a filtered block of video data;
- and
- output a picture of decoded video data that includes the filtered block.
5 more elements
A method of encoding video data, the method comprising:
- determining first neural network (NN) weights for a layer of a convolutional neural network (CNN) filter;
- deriving a quantization value for the layer of the CNN filter based on values of the first NN weights;
- converting the first NN weights to second NN weights based on the quantization value;
- filtering a first block of the video data using the second NN weights to produce a filtered block of the video data;
- storing a picture of decoded video data that includes the filtered block;
- and
- predicting a second block of the video data based on the stored picture.
4 more elements
Dependencies are inferred from the claim text.