Abstract: An image processing method, a related device, and a computer storage medium are provided. The method includes: obtaining a feature intensity image corresponding to a training image, where an intensity value of a pixel in the feature intensity image is used to indicate importance of the pixel for recognizing the training image, and resolution of the training image is the same as resolution of the feature intensity image; and occluding, based on the feature intensity image, a to-be-occluded region in the training image by using a preset window, to obtain a new image, where the to-be-occluded region includes a to-be-occluded pixel, and the new image is used to update an image recognition model. According to the embodiments of the present application, a prior-art problem that a model has low accuracy and relatively poor generalization performance because of limited training data can be resolved.

Abstract: This application provides a skin color detection method and apparatus. The skin color detection method includes: obtaining a face image (101); determining a face key point (102) in the face image; determining a skin color estimation region of interest (Region Of Interest, ROI) and an illumination estimation region of interest ROI (103) in the face image based on the face key point; obtaining a detected skin color value (104) corresponding to the skin color estimation region of interest; obtaining a detected illumination color value (105) corresponding to the illumination estimation region of interest; and using the detected skin color value and the detected illumination color value as feature input of a skin color estimation model, and obtaining a corrected skin color value (106) output by the skin color estimation model.

Abstract: Embodiments of the present invention disclose an image processing method, a related device, and a computer storage medium. The method includes: obtaining a feature intensity image corresponding to a training image, where an intensity value of a pixel in the feature intensity image is used to indicate importance of the pixel for recognizing the training image, and resolution of the training image is the same as resolution of the feature intensity image; and occluding, based on the feature intensity image, a to-be-occluded region in the training image by using a preset window, to obtain a new image, where the to-be-occluded region includes a to-be-occluded pixel, and the new image is used to update an image recognition model. According to the embodiments of the present invention, a prior-art problem that a model has low accuracy and relatively poor generalization performance because of limited training data can be resolved.