Scene Text Recognition
93 papers with code • 11 benchmarks • 19 datasets
See Scene Text Detection for leaderboards in this task.
Libraries
Use these libraries to find Scene Text Recognition models and implementationsMost implemented papers
SSD: Single Shot MultiBox Detector
Experimental results on the PASCAL VOC, MS COCO, and ILSVRC datasets confirm that SSD has comparable accuracy to methods that utilize an additional object proposal step and is much faster, while providing a unified framework for both training and inference.
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
In this paper, we investigate the problem of scene text recognition, which is among the most important and challenging tasks in image-based sequence recognition.
What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis
Many new proposals for scene text recognition (STR) models have been introduced in recent years.
FOTS: Fast Oriented Text Spotting with a Unified Network
Incidental scene text spotting is considered one of the most difficult and valuable challenges in the document analysis community.
Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition
Recognizing irregular text in natural scene images is challenging due to the large variance in text appearance, such as curvature, orientation and distortion.
A Multi-Object Rectified Attention Network for Scene Text Recognition
It decreases the difficulty of recognition and enables the attention-based sequence recognition network to more easily read irregular text.
MASTER: Multi-Aspect Non-local Network for Scene Text Recognition
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-decoder architecture.
Robust Scene Text Recognition with Automatic Rectification
We show that the model is able to recognize several types of irregular text, including perspective text and curved text.
Decoupled Attention Network for Text Recognition
To remedy this issue, we propose a decoupled attention network (DAN), which decouples the alignment operation from using historical decoding results.
Primitive Representation Learning for Scene Text Recognition
In this paper, we propose a primitive representation learning method that aims to exploit intrinsic representations of scene text images.