Microexpression-based image recognition method and apparatus, and related device

An electronic device, comprising:

• a processor and a memory,
• the processor being connected to the memory, the memory being configured to store a plurality of program instructions, and the processor being configured to execute the plurality of program instructions to perform a plurality of operations including:
• inputting an original expression image belonging to a first expression type into an image augmentation model, the original expression image belonging to the first expression type being an image comprising a microexpression of a person, the image augmentation model being obtained by training with a sample expression image belonging to the first expression type and a sample expression image belonging to a second expression type, and an expression intensity of the sample expression image belonging to the second expression type being greater than an expression intensity of the sample expression image belonging to the first expression type;
• augmenting, in the image augmentation model, an expression feature of the microexpression of the person in the original expression image, to obtain a target expression image belonging to the second expression type;
• and
• recognizing an expression attribute type corresponding to the target expression image, and determining the expression attribute type corresponding to the target expression image as an expression attribute type corresponding to the original expression image.

A non-transitory computer-readable storage medium, storing a plurality of program instructions, the program instructions, when executed by a processor of an electronic device, causing the electronic device to perform a plurality of operations including:

• inputting an original expression image belonging to a first expression type into an image augmentation model, the original expression image belonging to the first expression type being an image comprising a microexpression of a person, the image augmentation model being obtained by training with a sample expression image belonging to the first expression type and a sample expression image belonging to a second expression type, and an expression intensity of the sample expression image belonging to the second expression type being greater than an expression intensity of the sample expression image belonging to the first expression type;
• augmenting, in the image augmentation model, an expression feature of the microexpression of the person in the original expression image, to obtain a target expression image belonging to the second expression type;
• and
• recognizing an expression attribute type corresponding to the target expression image, and determining the expression attribute type corresponding to the target expression image as an expression attribute type corresponding to the original expression image.