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Thanks @michalfaber,
I am wondering if still make sense to mask the outputs if we have already masks the input image before. If we remove the outputs mask, we don't still need two build two different graphs for training and testing?
The text was updated successfully, but these errors were encountered:
I experimented a little bit with masking the input image instead of the masking outputs. I didn't see a significant improvement so I left the model unchanged. The original paper says that masking improves the performance by 2.3 % but they were training their model much longer.
Thanks @michalfaber,
I am wondering if still make sense to mask the outputs if we have already masks the input image before. If we remove the outputs mask, we don't still need two build two different graphs for training and testing?
The text was updated successfully, but these errors were encountered: