The big complicated segmentation pipeline is a legacy from the time you had to do that, a few years ago. It's error prone, and even at it's best it robs the model of valuable context. You need that context if you want to take the step to handwriting. If you go to a group of human experts to help you decipher historical handwriting, the first thing they will tell you is that they need the whole document for context, not just the line or word you're interested in.
We need to do end to end text recognition. Not "character recognition", it's not the characters we care about. Evaluating models with CER is also a bad idea. It frustrates me so much that text recognition is remaking all the mistakes of machine translation from 15+ years ago.
We need to do end to end text recognition. Not "character recognition", it's not the characters we care about. Evaluating models with CER is also a bad idea. It frustrates me so much that text recognition is remaking all the mistakes of machine translation from 15+ years ago.