I agree, this sounds like a somewhat plausible explanations. We already know that the nets largely take their cues from local image features (fur, eyes, etc) source 1. But that ‘image correctness’ on pixel-level would matter that much for a network?
I guess we have seen that ‘pixel correctness’ matters a lot in some adverserial attacks source1 source2
Is there a way to test for this? The only way I can think of right now would be to train on images where we delete green pixels corresponding to 50% of the original green pixels in the bayer filters, and interpolate it back. I see a few problems with this approach tho…