Image processing system, image processing method, and program

One or more non-transitory computer-readable media that store instructions which, when executed by one or more computer processors, cause the one or more computer processors to perform operations comprising;

• obtaining an n-th processing target frame, n being a natural number equal to or greater than 2, the target frame indicating, from a predetermined viewpoint, a virtual space in which one or more objects represented by three-dimensional data are arranged,
• obtaining an n-th input frame in reference to the n-th processing target frame,
• inputting the n-th input frame and (n-1)-th auxiliary information regarding features of first through (n-1)-th input frames to a first machine learning model to obtain n-th accumulated feature information indicating features of the first through n-th input frames that is to be output from the first machine learning model and an n-th estimated frame,
• obtaining n-th virtual space information that is information regarding the virtual space available for deciding a pixel value of each pixel of the n-th processing target frame,
• obtaining (n-1)-th depth information indicating a depth of each pixel of an (n-1)-th processing target frame and n-th depth information indicating a depth of each pixel of the n-th processing target frame,
• identifying an n-th appearing pixel that is a pixel among pixels of the n-th processing target frame and that is a pixel in which a whole or part of the object that is not displayed in the (n-1)-th processing target frame is displayed, in reference to the (n-1)-th depth information and the n-th depth information, and
• obtaining n-th auxiliary information in reference to at least the n-th appearing pixel, the n-th virtual space information, the n-th accumulated feature information, and a second machine learning model.

A computer-implemented method comprising:

• obtaining an n-th processing target frame, n being a natural number equal to or greater than 2, the target frame indicating, from a predetermined viewpoint, a virtual space in which one or more objects represented by three-dimensional data are arranged,
• obtaining an n-th input frame in reference to the n-th processing target frame,
• inputting the n-th input frame and (n-1)-th auxiliary information regarding features of first through (n-1)-th input frames to a first machine learning model to obtain n-th accumulated feature information indicating features of the first through n-th input frames that is to be output from the first machine learning model and an n-th estimated frame,
• obtaining n-th virtual space information that is information regarding the virtual space available for deciding a pixel value of each pixel of the n-th processing target frame
• obtaining (n-1)-th depth information indicating a depth of each pixel of an (n-1)-th processing target frame and n-th depth information indicating a depth of each pixel of the n-th processing target frame,
• identifying an n-th appearing pixel that is a pixel among pixels of the n-th processing target frame and that is a pixel in which a whole or part of the object that is not displayed in the (n-1)-th processing target frame is displayed, in reference to the (n-1)-th depth information and the n-th depth information, and
• obtaining n-th auxiliary information in reference to at least the n-th appearing pixel, the n-th virtual space information, the n-th accumulated feature information, and a second machine learning model.