Optical Character Recognition
Leaderboards
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
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Subtasks
Greatest papers with code
Attention-based Extraction of Structured Information from Street View Imagery
We present a neural network model - based on CNNs, RNNs and a novel attention mechanism - which achieves 84. 2% accuracy on the challenging French Street Name Signs (FSNS) dataset, significantly outperforming the previous state of the art (Smith'16), which achieved 72. 46%.
Adapting the Tesseract Open Source OCR Engine for Multilingual OCR
We describe efforts to adapt the Tesseract open source OCR engine for multiple scripts and languages.
End-to-End Interpretation of the French Street Name Signs Dataset
We introduce the French Street Name Signs (FSNS) Dataset consisting of more than a million images of street name signs cropped from Google Street View images of France.
#3 best model for
Optical Character Recognition
on FSNS - Test
COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images
The goal of COCO-Text is to advance state-of-the-art in text detection and recognition in natural images.
OBJECT RECOGNITION OPTICAL CHARACTER RECOGNITION SCENE TEXT DETECTION SCENE UNDERSTANDING
Image-to-Markup Generation with Coarse-to-Fine Attention
ICML 2017
• da03/Attention-OCR
• 
We present a neural encoder-decoder model to convert images into presentational markup based on a scalable coarse-to-fine attention mechanism.
ASTER: An Attentional Scene Text Recognizer with Flexible Rectification
SCENE text recognition has attracted great interest from the academia and the industry in recent years owing to its importance in a wide range of applications.
STN-OCR: A single Neural Network for Text Detection and Text Recognition
• Bartzi/stn-ocr
• 
In contrast to most existing works that consist of multiple deep neural networks and several pre-processing steps we propose to use a single deep neural network that learns to detect and recognize text from natural images in a semi-supervised way.
#3 best model for
Scene Text Detection
on ICDAR 2013
OPTICAL CHARACTER RECOGNITION SCENE TEXT DETECTION SCENE TEXT RECOGNITION
E2E-MLT - an Unconstrained End-to-End Method for Multi-Language Scene Text
An end-to-end trainable (fully differentiable) method for multi-language scene text localization and recognition is proposed.