This article mention gradually increasing image size during training. https://www.fast.ai/2018/08/10/fastai-diu-imagenet/ You need to be using adaptive pooling to take into account the different image sizes…
But I am wondering how this is implemented in terms of image resizing scheduling. Do they first fit one epoch with a specific size, then increase the size a little bit for the next epoch like it is shown in the courses, or are they using something more clever like gradually increasing the image size while fitting one epoch? I would be interested in finding more information about this and how this could be implemented in fastai.
Thanks!