A method for acquiring a three-dimensional face of a user, comprising: acquiring a plurality of two-dimensional face images of the user captured from a plurality of angles; generating a skin texture map by fusing the plurality of 2D face images; detecting a two-dimensional face image captured from a front side, by an image recognition technology, to acquire 2D facial feature points, wherein the face image captured from the front side is selected from the plurality of 2D face images captured from the plurality of angles; being characterized by: matching the 2D facial feature points with facial feature points of a pre-stored 3D face model, wherein when distances and positional relationship among the 2D facial feature points are matched with distances and positional relationship among the facial feature points of the pre-stored 3D face model, the 2D facial feature points match the facial feature points of the pre-stored 3D face model; in response to that the 2D facial feature points match the facial feature points of the pre-stored 3D face model, rendering the pre-stored 3D face model with the skin texture map to acquire a new 3D face; in response to that the 2D facial feature points do not match the facial feature points of the pre-stored 3D face model, acquiring depth information of the user's face; and performing 3D reconstruction based on the depth information and the plurality of 2D face images, to acquire a reconstructed 3D face model; and rendering the reconstructed 3D face model with the skin texture map to acquire the 3D face. acquiring a plurality of two-dimensional face images of the user captured from a plurality of angles; generating a skin texture map by fusing the plurality of 2D face images; detecting a two-dimensional face image captured from a front side, by an image recognition technology, to acquire 2D facial feature points, wherein the face image captured from the front side is selected from the plurality of 2D face images captured from the plurality of angles; being characterized by: matching the 2D facial feature points with facial feature points of a pre-stored 3D face model, wherein when distances and positional relationship among the 2D facial feature points are matched with distances and positional relationship among the facial feature points of the pre-stored 3D face model, the 2D facial feature points match the facial feature points of the pre-stored 3D face model; in response to that the 2D facial feature points match the facial feature points of the pre-stored 3D face model, rendering the pre-stored 3D face model with the skin texture map to acquire a new 3D face; in response to that the 2D facial feature points do not match the facial feature points of the pre-stored 3D face model, acquiring depth information of the user's face; and performing 3D reconstruction based on the depth information and the plurality of 2D face images, to acquire a reconstructed 3D face model; and rendering the reconstructed 3D face model with the skin texture map to acquire the 3D face. matching the 2D facial feature points with facial feature points of a pre-stored 3D face model, wherein when distances and positional relationship among the 2D facial feature points are matched with distances and positional relationship among the facial feature points of the pre-stored 3D face model, the 2D facial feature points match the facial feature points of the pre-stored 3D face model; in response to that the 2D facial feature points match the facial feature points of the pre-stored 3D face model, rendering the pre-stored 3D face model with the skin texture map to acquire a new 3D face; in response to that the 2D facial feature points do not match the facial feature points of the pre-stored 3D face model, acquiring depth information of the user's face; and performing 3D reconstruction based on the depth information and the plurality of 2D face images, to acquire a reconstructed 3D face model; and rendering the reconstructed 3D face model with the skin texture map to acquire the 3D face.