Linguistic knowledge is of great benefit to scene text recognition. However, how to effectively
model linguistic rules in end-to-end deep networks remains a research challenge. In this …

In this paper, we abandon the dominant complex language model and rethink the linguistic
learning process in the scene text recognition. Different from previous methods considering …

Scene text image contains two levels of contents: visual texture and semantic information.
Although the previous scene text recognition methods have made great progress over the …

The exploration of linguistic information promotes the development of scene text recognition
task. Benefiting from the significance in parallel reasoning and global relationship capture …

There are already some text-based visual question answering (TextVQA) benchmarks for
developing machine's ability to answer questions based on texts in images in recent years …

Scene text recognition has attracted great interests from the computer vision and pattern
recognition community in recent years. State-of-the-art methods use concolutional neural …

Perceiving text is crucial to understand semantics of outdoor scenes and hence is a critical
requirement to build intelligent systems for driver assistance and self-driving. Most of the …

Most existing video text spotting benchmarks focus on evaluating a single language and
scenario with limited data. In this work, we introduce a large-scale, Bilingual, Open World …

Scene text information extraction plays an important role in many computer vision
applications. Most features in existing text extraction algorithms are only applicable to one …

Recently, video text detection, tracking, and recognition in natural scenes are becoming very
popular in the computer vision community. However, most existing algorithms and …