CPC G06T 7/11 (2017.01) [G06F 18/213 (2023.01); G06F 18/24 (2023.01); G06T 7/73 (2017.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01)] | 20 Claims |
1. A computer-implemented method comprising:
obtaining an image comprising a plurality of pixels;
generating, using a first portion of a machine-learned segmentation model, an initial distance function indicative of a distance of a respective pixel, of the plurality of pixels, to a predicted nearest boundary of an object depicted in the image;
generating, using a second portion of the machine-learned segmentation model, an object feature representation that comprises a feature embedding for the image;
determining, using an energy function, a final distance function based on the initial distance function and the object feature representation,
wherein the final distance function indicates that the respective pixel is associated with a background of the image or that the respective pixel is associated with the object depicted in the image; and
determining an instance segmentation mask for the image based on the final distance function.
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