| CPC G06T 7/11 (2017.01) [G06T 7/194 (2017.01); G06T 7/90 (2017.01); G06T 2207/20081 (2013.01); G06T 2207/20112 (2013.01)] | 15 Claims |

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1. A method for auto segmentation executed by an apparatus for auto segmentation, the method comprising:
receiving a first object image including an object labeled with a bounding box, which is a pre-learning target;
learning a segmentation model by classifying an object and a background from the bounding box of the received first object image; and
segmenting an object from a second object image, which is an identification target, using the learned segmentation model,
wherein the learning a segmentation model calculates a mask loss by summing a first loss calculated by using a mask and a bounding box predicted in the first object image and a second loss calculated by using a mask predicted in the first object image and a color similarity map between individual pixels and their neighboring pixels within the bounding box and learns the segmentation model using the calculated mask loss.
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