A computer implemented reprojection method for generating reprojected image data to be displayed on an extended reality, XR, device, wherein the reprojection method comprises the following steps: - determining momentary position data, wherein the momentary position data is associated with a momentary position of the XR device; - generating preliminary image data based on the momentary position data, wherein the preliminary image data corresponds to at least one XR image to be displayed on the XR device; - determining updated position data, wherein the updated position data is associated with a position of the XR device at the time at which the at least one XR image is to be displayed; - inputting the momentary position data, the preliminary image data, and the updated position data into a machine-learning module, wherein the machine-learning module comprises a machine-learning model that is pre-trained to reproject the preliminary image data based on the momentary position data, the preliminary image data, and the updated position data; and - reprojecting the preliminary image data by means of the machine-learning module, thereby generating reprojected image data, wherein the reprojected image data corresponds to at least one reprojected XR image to be displayed on the XR device; characterized in that the machine-learning model is trained with at least two training data sets, wherein a first one of the at least two training data sets comprises first image data associated with a first position of the XR device, wherein a second one of the at least two training data sets comprises image data associated with a second position of the XR device, and wherein the machine-learning model is trained by means of the following steps: - inputting position data corresponding to the first position, the first image data, and position data corresponding to the second position into the machine-learning module (step T2); - reprojecting the first image data by means of the machine-learning module, thereby generating reprojected image data (step T3); - comparing the reprojected image data with the second image data; - determining an error measure based on the comparison of the reprojected image data with the second image data (step T4); and - adapting weighting factors of the machine-learning model such that the error measure is reduced (step T5). - determining momentary position data, wherein the momentary position data is associated with a momentary position of the XR device; - generating preliminary image data based on the momentary position data, wherein the preliminary image data corresponds to at least one XR image to be displayed on the XR device; - determining updated position data, wherein the updated position data is associated with a position of the XR device at the time at which the at least one XR image is to be displayed; - inputting the momentary position data, the preliminary image data, and the updated position data into a machine-learning module, wherein the machine-learning module comprises a machine-learning model that is pre-trained to reproject the preliminary image data based on the momentary position data, the preliminary image data, and the updated position data; and - reprojecting the preliminary image data by means of the machine-learning module, thereby generating reprojected image data, wherein the reprojected image data corresponds to at least one reprojected XR image to be displayed on the XR device; - inputting position data corresponding to the first position, the first image data, and position data corresponding to the second position into the machine-learning module (step T2); - reprojecting the first image data by means of the machine-learning module, thereby generating reprojected image data (step T3); - comparing the reprojected image data with the second image data; - determining an error measure based on the comparison of the reprojected image data with the second image data (step T4); and - adapting weighting factors of the machine-learning model such that the error measure is reduced (step T5).