Learning device, search device, learning method, search method, learning program, and search program

A learning apparatus comprising circuitry configured to execute a method comprising:

• calculating a second similarity for a combination of reference images by using information on features different from feature vectors of the labeled reference images, the second similarity being calculated as a similarity determined using the information on the features,
• the reference images including a basic image as a reference of the labeling, a similar image that is the reference image similar to the basic image, and a dissimilar image that is the reference image dissimilar to the basic image;
• and
• updating a parameter of a neural network such that a margin increases as a second similarity between the basic image and the dissimilar image increases relative to a second similarity between the basic image and the similar image, the parameter being updated by using a loss function including a first similarity between the feature vector of the basic image and the feature vector of the similar image, a first similarity between the feature vector of the basic image and the feature vector of the dissimilar image, and the margin based on the second similarity between the basic image and the similar image and the second similarity between the basic image and the dissimilar image, the feature vectors being outputted from the neural network for receiving a predetermined image and outputting the feature vectors.

A computer-implemented method for retrieving, comprising:

• receiving a query image to be retrieved;
• calculating a first similarity as a similarity between feature vectors, the first similarity being calculated between a feature vector extracted from the query image through learned feature extraction for outputting the feature vector and a feature vector extracted from reference images labeled by the feature extraction;
• calculating a second similarity as a similarity determined using information on features, based on information on a feature different from the feature vector of the query image and information on the features of the reference images;
• and
• calculating an integrated similarity by integrating the calculated first similarity and the calculated second similarity, wherein
• for similarities between a basic image, an image similar to the basic image, and an image dissimilar to the basic image of the reference images, at least the feature extraction is learned such that a margin based on a second similarity between the basic image and the similar image and a second similarity between the basic image and the dissimilar image increases as the second similarity between the basic image and the dissimilar image increases relative to the second similarity between the basic image and the similar image.