Computer architecture for artificial intelligence model training

A learning method performed by at least one processor, comprising:

• acquiring training data including, as an input portion, a training target image showing a training target object and a training reference image showing a training reference object, and including, as a ground truth portion, ground truth information for processing the training target image so that a training target pose of the training target object coincides with a training reference pose of the training reference object;
• and
• executing, based on the training data, training of at least one of:
• a first model configured to calculate a first training target feature of the training target image and a first training reference feature of the training reference image, and to output first training processing information for processing the training target image so that the training target pose coincides with the training reference pose, based on the first training target feature and the first training reference feature;
• or a second model configured to calculate a second training target feature of the training target image and a second training reference feature of the training reference image, and to output second training processing information for processing the training target image so that the training target pose coincides with the training reference pose, based on the first training processing information, the second training target feature, and the second training reference feature.

A non-transitory computer readable storage medium storing a program that causes a computer to:

• acquire training data including, as an input portion, a training target image showing a training target object and a training reference image showing a training reference object, and including, as a ground truth portion, ground truth information for processing the training target image so that a training target pose of the training target object coincides with a training reference pose of the training reference object;
• and
• execute, based on the training data, training of at least one of:
• a first model configured to calculate a first training target feature of the training target image and a first training reference feature of the training reference image, and to output first training processing information for processing the training target image so that the training target pose coincides with the training reference pose, based on the first training target feature and the first training reference feature;
• or a second model configured to calculate a second training target feature of the training target image and a second training reference feature of the training reference image, and to output second training processing information for processing the training target image so that the training target pose coincides with the training reference pose, based on the first training processing information, the second training target feature, and the second training reference feature.