Is RoI Pooling appropriate to retrieve fine details from objects of varying sizes?

I’m using a RoI Pooling after a CNN that extract features from images of varying sizes, containing defects I want to classify. The images and defects sizes range from a couple of pixels to ~100 pixels.

As I understand it, this way of pooling may lose some of the finer details, especially in big images for which the pooling is rougher. Is my intuition correct and is there any other way of retrieving a fixed sized feature vector?

Technical details: I’m working with the Keras library in Python, and using the VGG19 architecture pre-trained on the ‘ImageNet’ dataset for transfer learning.