With the rise and development of deep learning, computer vision has been tremendously
transformed and reshaped. As an important research area in computer vision, scene text …

The history of text can be traced back over thousands of years. Rich and precise semantic
information carried by text is important in a wide range of vision-based application …

We present a new dataset for Visual Question Answering (VQA) on document images called
DocVQA. The dataset consists of 50,000 questions defined on 12,000+ document images …

Recently, models based on deep neural networks have dominated the fields of scene text
detection and recognition. In this paper, we investigate the problem of scene text spotting …

A challenging aspect of scene text recognition is to handle text with distortions or irregular
layout. In particular, perspective text and curved text are common in natural scenes and are …

Automated recognition of texts in scenes has been a research challenge for years, largely
due to the arbitrary text appearance variation in perspective distortion, text line curvature …

Irregular text is widely used. However, it is considerably difficult to recognize because of its
various shapes and distorted patterns. In this paper, we thus propose a multi-object rectified …

Image descriptions can help visually impaired people to quickly understand the image
content. While we made significant progress in automatically describing images and optical …

In this paper, we propose Text-Aware Pre-training (TAP) for Text-VQA and Text-Caption
tasks. These two tasks aim at reading and understanding scene text in images for question …

Scene text recognition has been a hot research topic in computer vision due to its various
applications. The state of the art is the attention-based encoder-decoder framework that …