As a result,z is fed into the classifier, and the overall loss of CASE is defined as follows: Selective Refinement Lastly, CASE aims to refine only when the perturbation can refine the translation.
if the translation is already good, CASE avoids a refinement, by parameterizing refinement with α set to be near zero.