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IIGROUP / MANIQA

[CVPRW 2022] MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
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weighting branch and scoring branch #26

Closed dmumtaz closed 1 year ago

dmumtaz commented 1 year ago

Hi

In your paper, it is shown that the final quality score is obtained my combining the weighting branch and scoring branch. The only difference between the two branches seems to be the final activation function i.e. ReLu and Sigmoid. Can you please share the intuition regarding the architecture of the two branches?

TianheWu commented 1 year ago

In the competition, we regard that different patches has different weights for the final assessment. So, we add Sigmoid function to learn the patches weight.