Scene Text Recognition
144 papers with code • 15 benchmarks • 29 datasets
See Scene Text Detection for leaderboards in this task.
Benchmarks
These leaderboards are used to track progress in Scene Text Recognition
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Libraries
Use these libraries to find Scene Text Recognition models and implementations
ICDAR 2013
COCO-Text
ICDAR 2003
SVT
TextOCR
RCTW-17
HOST
UFPR-ALPR
Most implemented papers
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
clovaai/deep-text-recognition-benchmark
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ICCV 2019
Many new proposals for scene text recognition (STR) models have been introduced in recent years.
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.
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
microsoft/unilm
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Text recognition is a long-standing research problem for document digitalization.
FOTS: Fast Oriented Text Spotting with a Unified Network
jiangxiluning/FOTS.PyTorch
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CVPR 2018
Incidental scene text spotting is considered one of the most difficult and valuable challenges in the document analysis community.
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
PaddlePaddle/PaddleOCR
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CVPR 2016
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
Canjie-Luo/Scene-Text-Image-Transformer
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To remedy this issue, we propose a decoupled attention network (DAN), which decouples the alignment operation from using historical decoding results.
RobustScanner: Dynamically Enhancing Positional Clues for Robust Text Recognition
open-mmlab/mmocr
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ECCV 2020
Theoretically, our proposed method, dubbed \emph{RobustScanner}, decodes individual characters with dynamic ratio between context and positional clues, and utilizes more positional ones when the decoding sequences with scarce context, and thus is robust and practical.
