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 …

Scene text recognition is a hot research topic in computer vision. Recently, many recognition
methods based on the encoder-decoder framework have been proposed, and they can …

Recognizing irregular text in natural scene images is challenging due to the large variance
in text appearance, such as curvature, orientation and distortion. Most existing approaches …

In this paper we present a deployed, scalable optical character recognition (OCR) system,
which we call Rosetta, designed to process images uploaded daily at Facebook scale …

Reading text in the wild is a very challenging task due to the diversity of text instances and
the complexity of natural scenes. Recently, the community has paid increasing attention to …

Scene text recognition is a challenging task due to diverse variations of text instances in
natural scene images. Conventional methods based on CNN-RNN-CTC or encoder …

Low-resolution text images are often seen in natural scenes such as documents captured by
mobile phones. Recognizing low-resolution text images is challenging because they lose …

Attention-based scene text recognizers have gained huge success, which leverages a more
compact intermediate representation to learn 1d-or 2d-attention by a RNN-based encoder …

Abstract Connectionist Temporal Classification (CTC) and attention mechanism are two
main approaches used in recent scene text recognition works. Compared with attention …