A supersampling method and apparatus are provided. The method includes: receiving a low-resolution three-dimensional (3D) image comprising a current frame and receiving a previous frame preceding the current frame; generating a low-resolution partial image by repeatedly sampling sub-pixel regions of the current frame; warping a high-resolution image, of the previous frame, which has been outputted from a neural network, to a current view corresponding to the current frame; replacing a partial region of the warped high-resolution image of the previous frame with image data from the low-resolution partial image; and generating a high-resolution image of the current frame by applying the high-resolution image of the previous frame, in which the partial region has been replaced, to the neural network.