High resolution human imaging using neural network is described. In one example, a described method comprises: assembling a k1-dimensional (k1-D) imaging matrix by a processor based on arranging and concatenating a plurality of k2-dimensional (k2-D) input imaging matrices; encoding the k1-D imaging matrix by an encoder, which is a k1-D encoding neural network, to generate a (k1+k3)-D first intermediate matrix; generating a (k2+k3)-D second intermediate matrix based on the (k1+k3)-D first intermediate matrix; and decoding the (k2+k3)-D second intermediate matrix by a decoder, which is a k2-D decoding neural network, to generate a k2-D output imaging matrix. There is at least one skip connection between the encoder and the decoder. An imaging resolution of the k2-D output imaging matrix is greater than the imaging resolution of any one of the plurality of k2-D input imaging matrices.