Patent ID: 11887348
Assignee: SAMSUNG ELECTRONICS CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 13:
14. A processor-implemented training method comprising:
acquiring a (1-1)-th feature vector by encoding a first image and first pose information corresponding to the first image;
acquiring a (1-2)-th feature vector by encoding a second image corresponding to a target image of the first image and second pose information corresponding to the second image;
training an encoder to maintain an identity of an object included in each of the first image and the second image, regardless of a pose of the object, based on a difference between the (1-1)-th feature vector and the (1-2)-th feature vector;
acquiring a second feature vector from an intermediate layer of the encoder;
converting the first pose information to correspond to the intermediate layer;
generating a weight map including a position in which a target component is to be generated in the second image which has a pose corresponding to rotation information by applying the second feature vector, the converted first pose information and the rotation information to a first neural network;
separating a target feature vector corresponding to the target component from the second feature vector;
generating an assistant feature vector which represents the target component corresponding to the pose in the position in which the target component is to be generated, by combining the weight map and the target feature vector;
generating a third image by decoding, with a decoder, the (1-1)-th feature vector based on the assistant feature vector; and
training the first neural network, the encoder and the decoder based on the second image and the third image.