| CPC G06T 5/50 (2013.01) [G06V 10/454 (2022.01); G06V 10/513 (2022.01); G06V 10/751 (2022.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20221 (2013.01)] | 18 Claims |

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1. A method for image processing, comprising:
encoding a content image and a style image using a machine learning model to obtain content features and style features, wherein the content image includes a first object having a first appearance attribute and the style image includes a second object having a second appearance attribute;
computing a pixel-wise similarity score between a pixel from the content image and a pixel from the style image based on the content features and the style features;
including the pixel from the content image in a sparse set of pixels of the content image based on the pixel-wise similarity score;
aligning the content features and the style features to obtain a sparse correspondence map that indicates a correspondence between the sparse set of pixels of the content image and corresponding pixels of the style image; and
generating a hybrid image based on the sparse correspondence map, wherein the hybrid image depicts the first object having the second appearance attribute.
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