DetectionTeamUCAS / DetectionTeamUCAS/NAS_FPN_Tensorflow

How do you know the positions of two feature maps in Global pooling operations?

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Thanks for your work!

In the Global pooling operation, the roles of two input feature maps are not equivalent. Only given Figure 6 and Figure 7 in the paper, I cannot know which feature map play the role of channel attention. I fail to find any latent rule from your realization. I wonder how do you determine the positions of two feature maps at every Global pooling operation. Did you ask the authors?

Another little question is why you take the mean value in Global pooling operation while it uses max pooling according to the paper.

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