  This paper proposes a new method, OFA-OCR, to transfer multimodal pretrained
models to text recognition. Specifically, we recast text recognition as image
captioning and directly transfer a unified vision-language pretrained model to
the end task. Without pretraining on large-scale annotated or synthetic text
recognition data, OFA-OCR outperforms the baselines and achieves
state-of-the-art performance in the Chinese text recognition benchmark.
Additionally, we construct an OCR pipeline with OFA-OCR, and we demonstrate
that it can achieve competitive performance with the product-level API. The
code (https://github.com/OFA-Sys/OFA) and demo
(https://modelscope.cn/studios/damo/ofa_ocr_pipeline/summary) are publicly
available.
