introduced for exactly resolving this problem in types of data like images or higher order tensors and they also combine this together with learned positional encodings which we've also seen um time and time again throughout the kind of transformer and attention literature so the combination of axial attention these learn positional embeddings allows them to replace the resnet backbone that usually is found in panoptix segmentation models with the with a standalone attention so they build models that are partial