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@TouqeerAhmad I first use the frequency transform operator to extract the different components of the image, and then send it to several convolutional layers, and then perform the inverse transform, and the checkerboard effect occurs.
I'm not sure if it's the convolution that messes up the high and low frequency components, since convolution operates on the channel dimension.
Good job!
I met the checkerboard effect during my training. Has someone encountered this, too?
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