Using checkerboard rendering and deconvolution to eliminate checkerboard artifacts in images generated by neural networks

摘要

The images generated by deep neural networks is clear, but when the observers watch very closely at these images, they often see some checkerboard patterns of artifacts, in this paper, we analyzed the causes of this phenomenon of checkerboard artifacts, and we have found a solution to the problem, deconvolution and checkerboard rendering can provide a method to eliminate the checkerboard artifacts and make the images more distinct. Experimental results show that we have provided to use solution that improves the quality of many approaches to generating images with deep neural networks.