Information surrounds people in modern life. Text is a very efficient type of information that people use for communication for centuries. However, automated text-in-the-wild recognition remains a challenging problem. The major limitation for a DL system is the lack of training data. For the competitive performance, training set must contain many samples that replicate the real-world cases. While there are many high-quality datasets for English text recognition; there are no available datasets for Russian language. In this paper, we present a large-scale human-labeled dataset for Russian text recognition in-the-wild. We also publish a synthetic dataset and code to reproduce the generation process
@article{arxiv.2303.16531,
title = {RusTitW: Russian Language Text Dataset for Visual Text in-the-Wild Recognition},
author = {Igor Markov and Sergey Nesteruk and Andrey Kuznetsov and Denis Dimitrov},
journal= {arXiv preprint arXiv:2303.16531},
year = {2023}
}