Training method of image-text matching model, bi-directional search method, and relevant apparatus

An apparatus, comprising:

• a memory storing computer program instructions;
• and a processor coupled to the memory and configured to execute the computer program instructions and perform a method including:
• extracting a global feature of an image sample, and extracting a local feature of the image sample;
• extracting a global feature of a text sample, and extracting a local feature of the text sample;
• and
• training an image-text matching model according to the global feature and the local feature of the image sample and according to the global feature and the local feature of the text sample,
• wherein the global feature of the image sample includes a feature of a fully connected layer of a convolutional neural network of the image sample, and wherein each node of the fully connected layer is connected to all nodes of a previous layer of the convolutional neural network.

A non-transitory computer-readable storage medium storing computer program instructions executable by at least one processor to perform a method including:

• extracting a global feature of an image sample, and extracting a local feature of the image sample;
• extracting a global feature of a text sample, and extracting a local feature of the text sample;
• and
• training an image-text matching model according to the global feature and the local feature of the image sample and according to the global feature and the local feature of the text sample,
• wherein the global feature of the image sample includes a feature of a fully connected layer of a convolutional neural network of the image sample, and wherein each node of the fully connected layer is connected to all nodes of a previous layer of the convolutional neural network.