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Keras implementation of Non-local Neural Networks

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Weight sharing

yunzhe-tao opened this issue · comments

commented

In the paper when adding multiple nonlocal blocks, I think the weight W_g in the affinity function f is shared for each nonlocal block. Is it true? If it's true, how to you implement this in your codes? Thanks

commented

I think the weight W_g in the affinity function f is shared for each nonlocal block.

Where is this? The paper has 0 instances of the words "share", "tied", "same" which would be used to discuss shared weights, so I don't think this is true.