Human body attribute recognition method and apparatus, electronic device, and storage medium

An apparatus for recognizing human body attributes, the apparatus comprising:

• a memory storing instructions;
• and
• a processor in communication with the memory, wherein, when the processor executes the instructions, the processor is configured to cause the apparatus to perform:
• acquiring a sample image of human body, the sample image containing a plurality of to-be-detected areas, the to-be-detected areas being labeled with true values of human body attributes,
• generating, through a recognition model, a heat map of the sample image and heat maps of the to-be-detected areas to obtain a global heat map and local heat maps corresponding to the sample image,
• fusing the global heat map and the local heat maps to obtain a fused image, and performing human body attribute recognition on the fused image to obtain predicted values of human body attribute of the sample image,
• determining a focus area of each type of human body attribute according to the global heat map and the local heat maps,
• correcting the recognition model by using the focus area, the true values of human body attributes, and the predicted values of human body attributes, and
• performing, based on the corrected recognition model, human body attribute recognition on a to-be-recognized image.

A non-transitory computer-readable storage medium storing computer-readable instructions, wherein, the computer-readable instructions, when executed by a processor, are configured to cause the processor to perform:

• acquiring a sample image of human body, the sample image containing a plurality of to-be-detected areas, the to-be-detected areas being labeled with true values of human body attributes;
• generating, through a recognition model, a heat map of the sample image and heat maps of the to-be-detected areas to obtain a global heat map and local heat maps corresponding to the sample image;
• fusing the global heat map and the local heat maps to obtain a fused image, and performing human body attribute recognition on the fused image to obtain predicted values of human body attribute of the sample image;
• determining a focus area of each type of human body attribute according to the global heat map and the local heat maps;
• correcting the recognition model by using the focus area, the true values of human body attributes, and the predicted values of human body attributes;
• and
• performing, based on the corrected recognition model, human body attribute recognition on a to-be-recognized image.