In the case of a deep CNN task, I do understand that sometimes image pre-processing techniques such as gaussian filtering and cropping can be helpful for deep CNN modeling. I wonder if it is also acceptable to be applied to testing data as well. I've always thought that test data should never be touched whatsoever so that the model performance can be evaluated accurately.
As a matter of fact, you do need to apply those filters, which you have used on training data, on your test as well!
The fact that you should not touch your test data, is about not using them in during the training, so the generalization is being done only using the train, so that when you evaluate on a test, you get a realistic performance and quality of your model.
Any filtering, like Gaussian, applied on train data, before injecting them to model training, should be done on the test data as well.
For cropping, it really depends on how you crop, and what you crop. If your photos have always the frames around them, and in the train dataset you crop to remove those, I highly suggest doing the same for the test