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The most prominent problem associated with the deconvolution layer is thepresence of checkerboard artifacts in output images and dense labels. To combatthis problem, smoothness constraints, post processing and differentarchitecture designs have been proposed. Odena et al. highlight three sourcesof checkerboard artifacts: deconvolution overlap, random initialization andloss functions. In this note, we proposed an initialization method forsub-pixel convolution known as convolution NN resize. Compared to sub-pixelconvolution initialized with schemes designed for standard convolution kernels,it is free from checkerboard artifacts immediately after initialization.Compared to resize convolution, at the same computational complexity, it hasmore modelling power and converges to solutions with smaller test errors.

Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize