A method for face image processing, performed by an apparatus for face image processing, comprising: acquiring first-key-point information of a first face image; performing position transformation on the first-key-point information to obtain second-key-point information conforming to a second facial geometric attribute, the second facial geometric attribute being different from a first facial geometric attribute corresponding to the first-key-point information; and performing facial texture coding processing by utilizing a neural network and the second-key-point information to obtain a second face image; characterized in that performing facial texture coding processing by utilizing the neural network and the second-key-point information to obtain the second face image comprises: generating a mask map of a target face based on the second-key-point information, values of pixels in a face image area in the mask map being a first predetermined value, values of pixels outside the face image area being a second predetermined value, and the face image area being defined by each second key point describing a facial contour; fusing the mask map and the first face image to generate a fifth face image, the face image area in the first face image being reserved in the fifth face image; generating a contour map of geometric attributes of a target face based on the second-key-point information, values of pixels on a contour line of each part in the contour map being a third predetermined value, values of pixels other than the pixels on the contour line of each part being a fourth predetermined value, and the contour line of each part being defined by second key points describing each face part; and inputting the fifth face image and the contour map into the neural network for facial texture coding to obtain the second face image. acquiring first-key-point information of a first face image; performing position transformation on the first-key-point information to obtain second-key-point information conforming to a second facial geometric attribute, the second facial geometric attribute being different from a first facial geometric attribute corresponding to the first-key-point information; and performing facial texture coding processing by utilizing a neural network and the second-key-point information to obtain a second face image; characterized in that performing facial texture coding processing by utilizing the neural network and the second-key-point information to obtain the second face image comprises: generating a mask map of a target face based on the second-key-point information, values of pixels in a face image area in the mask map being a first predetermined value, values of pixels outside the face image area being a second predetermined value, and the face image area being defined by each second key point describing a facial contour; fusing the mask map and the first face image to generate a fifth face image, the face image area in the first face image being reserved in the fifth face image; generating a contour map of geometric attributes of a target face based on the second-key-point information, values of pixels on a contour line of each part in the contour map being a third predetermined value, values of pixels other than the pixels on the contour line of each part being a fourth predetermined value, and the contour line of each part being defined by second key points describing each face part; and inputting the fifth face image and the contour map into the neural network for facial texture coding to obtain the second face image. generating a mask map of a target face based on the second-key-point information, values of pixels in a face image area in the mask map being a first predetermined value, values of pixels outside the face image area being a second predetermined value, and the face image area being defined by each second key point describing a facial contour; fusing the mask map and the first face image to generate a fifth face image, the face image area in the first face image being reserved in the fifth face image; generating a contour map of geometric attributes of a target face based on the second-key-point information, values of pixels on a contour line of each part in the contour map being a third predetermined value, values of pixels other than the pixels on the contour line of each part being a fourth predetermined value, and the contour line of each part being defined by second key points describing each face part; and inputting the fifth face image and the contour map into the neural network for facial texture coding to obtain the second face image.