Some result of Dissimilarity Visualization

I tried one potential method to visualize how two image embedding are different. Basicly, it tries to find which channel in embedding vector make negetive value in dot product of two embedding. Then, Showing the combination(weighted by how negetive they are) of activation map (before pooling layer) on those channel.

Here are some interesting example on HOTEL dataset:

It clear catch the different on the sink
This one catch the headboard
And this one focus on the lights.

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