providing a video image at a current time point;

dividing the video image at the current time point into a plurality of sub-regions;

inputting image feature information of the sub-regions and acquired user viewpoint feature information into a trained attention model for processing to obtain attention coefficients of the sub-regions indicating probability values at which user viewpoints at a next time point fall into the sub-regions;

rendering the sub-regions based on the attention coefficients of the sub-regions to obtain a rendered video image at the current time point;

inputting the attention coefficients of the sub-regions and the image feature information of the sub-regions into a trained user eyes trajectory prediction model for processing;

obtaining user eyes trajectory information in a current time period;

dividing, for video images at subsequent time points within the current time period, the video images at the subsequent time points into a plurality of sub-regions, calculating attention coefficients of the sub-regions in a video image at each of the subsequent time points within the current time period respectively based on the user eyes trajectory information in the current time period; and

rendering the corresponding sub-regions based on the attention coefficients of the sub-regions to obtain a rendered video image at each of the subsequent time points.