Deep learning based methods have achieved surprising progress in Scene Text Recognition (STR), one of classic problems in computer vision.
We introduce the bidirectional Scene Text Transformer (Bi-STET), a novel bidirectional STR method with a single decoder for bidirectional text decoding.
Most of these methods propose novel building blocks for neural networks.
Scene text recognition (STR) is the task of recognizing character sequences in natural scenes.
This paper reports the ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT) that consists of three major challenges: i) scene text detection, ii) scene text recognition, and iii) scene text spotting.
Recently, scene text recognition methods based on deep learning have sprung up in computer vision area.
Many new proposals for scene text recognition (STR) models have been introduced in recent years.
It decreases the difficulty of recognition and enables the attention-based sequence recognition network to more easily read irregular text.