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Dmitry Ulyanov, Andrea Vedaldi, Victor S. Lempitsky. Instance Normalization: The Missing Ingredient for Fast Stylization. CoRR abs/1607.08022 (2016)

In the context of stylization, Ulyanov et al. propose to use instance normalization instead of batch normalization. In detail, instance normalization does not compute the mean and standard deviation used for normalization over the current mini-batch in training. Instead, these statistics are computed per instance individually. This also has the benefit of having the same training and test procedure, meaning that normalization is the same in both cases – in contrast to batch normalization.

Also find this summary on ShortScience.org.

What is your opinion on the summarized work? Or do you know related work that is of interest? Let me know your thoughts in the comments below: