What is spatial transformer network (STN) and how does it learn geometric invariance?

STN learns spatial transformations to normalize input images within the network.

Spatial Transformer Networks introduce a differentiable module that predicts transformation parameters (translation, rotation, scaling) and applies them to input feature maps. This allows the network to learn invariance to geometric transformations without explicit preprocessing.