  Extracting Handwritten text is one of the most important components of
digitizing information and making it available for large scale setting.
Handwriting Optical Character Reader (OCR) is a research problem in computer
vision and natural language processing computing, and a lot of work has been
done for English, but unfortunately, very little work has been done for low
resourced languages such as Urdu. Urdu language script is very difficult
because of its cursive nature and change of shape of characters based on it's
relative position, therefore, a need arises to propose a model which can
understand complex features and generalize it for every kind of handwriting
style. In this work, we propose a transformer based Urdu Handwritten text
extraction model. As transformers have been very successful in Natural Language
Understanding task, we explore them further to understand complex Urdu
Handwriting.
