In this paper we propose an approach to lexicon-free recognition of text in scene images.
Our approach relies on a LSTM-based soft visual attention model learned from convolutional …

The recognition of text in natural scene images is a practical yet challenging task due to the
large variations in backgrounds, textures, fonts, and illumination conditions. In this paper, we …

Natural scene text recognition has proved to be challenging due to the unconstrained wild
conditions. In this paper, to solve this problem we propose a method which first detects and …

Scene text recognition has gained significant attention from the computer vision community
in recent years. Recognizing such text is a challenging problem, even more so than the …

Understanding text captured in real-world scenes is a challenging problem in the field of
visual pattern recognition and continues to generate a significant interest in the OCR …

Inspired by the success of Deep Learning based approaches to English scene text
recognition, we pose and bench-mark scene text recognition for three Indic scripts …

This paper presents Diffusion Model for Scene Text Recognition (DiffusionSTR), an end-to-
end text recognition framework using diffusion models for recognizing text in the wild. While …

This paper focuses on the problem of word detection and recognition in natural images. The
problem is significantly more challenging than reading text in scanned documents, and has …

Text signage as visual indicators in natural scene plays an important role in navigation and
notification in our daily life. Most previous methods of scene text extraction are developed …

Building robust recognizers for Arabic has always been challenging. We demonstrate the
effectiveness of an end-to-end trainable CNN-RNN hybrid architecture in recognizing Arabic …