Huh, cool find. I’m also curious. Link 29 to code.
Edit: Ok so I’m still not sure but one reason to freeze the batch norm is when the batch size is very low, like e.g. 1. I did try mask-rcnn at some point and remember that it was very GPU-memory intensive. I’m guessing they load the weights for their backbone and that batchnorm is already tuned to another dataset so that’s better than no batch norm? Again, speculation