OCR material

Papers

End-to-End Text Recognition with Convolutional Neural Networks

• paper: http://www.cs.stanford.edu/~acoates/papers/wangwucoatesng_icpr2012.pdf
• PhD thesis: http://cs.stanford.edu/people/dwu4/HonorThesis.pdf

Word Spotting and Recognition with Embedded Attributes

• paper: http://ieeexplore.ieee.org.sci-hub.org/xpl/articleDetails.jsp?arnumber=6857995&filter%3DAND%28p_IS_Number%3A6940341%29

Reading Text in the Wild with Convolutional Neural Networks

• arxiv: http://arxiv.org/abs/1412.1842
• homepage: http://www.robots.ox.ac.uk/~vgg/publications/2016/Jaderberg16/
• demo: http://zeus.robots.ox.ac.uk/textsearch/#/search/
• code: http://www.robots.ox.ac.uk/~vgg/research/text/

Deep structured output learning for unconstrained text recognition

• intro: “propose an architecture consisting of a character sequence CNN and an N-gram encoding CNN which act on an input image in parallel and whose outputs are utilized along with a CRF model to recognize the text content present within the image.”
• arxiv: http://arxiv.org/abs/1412.5903

Deep Features for Text Spotting

• paper: http://www.robots.ox.ac.uk/~vgg/publications/2014/Jaderberg14/jaderberg14.pdf
• bitbucket: https://bitbucket.org/jaderberg/eccv2014_textspotting
• gitxiv: http://gitxiv.com/posts/uB4y7QdD5XquEJ69c/deep-features-for-text-spotting

Reading Scene Text in Deep Convolutional Sequences

• arxiv: http://arxiv.org/abs/1506.04395

DeepFont

DeepFont: Identify Your Font from An Image

• arxiv: http://arxiv.org/abs/1507.03196

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

• arxiv: http://arxiv.org/abs/1507.05717
• github: https://github.com/bgshih/crnn

Recursive Recurrent Nets with Attention Modeling for OCR in the Wild

• arxiv: http://arxiv.org/abs/1603.03101

Writer-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networks

• arxiv: http://arxiv.org/abs/1604.00974

DeepText

DeepText: A Unified Framework for Text Proposal Generation and Text Detection in Natural Images

• arxiv: http://arxiv.org/abs/1605.07314

End-to-End Interpretation of the French Street Name Signs Dataset

• paper: http://link.springer.com/chapter/10.1007%2F978-3-319-46604-0_30
• github: https://github.com/tensorflow/models/tree/master/street

End-to-End Subtitle Detection and Recognition for Videos in East Asian Languages via CNN Ensemble with Near-Human-Level Performance

• arxiv: https://arxiv.org/abs/1611.06159

Smart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Reading

• arxiv: https://arxiv.org/abs/1611.07385

Text Detection

Object Proposals for Text Extraction in the Wild

• intro: ICDAR 2015
• arxiv: http://arxiv.org/abs/1509.02317
• github: https://github.com/lluisgomez/TextProposals

Text-Attentional Convolutional Neural Networks for Scene Text Detection

• arxiv: http://arxiv.org/abs/1510.03283

Accurate Text Localization in Natural Image with Cascaded Convolutional Text Network

• arxiv: http://arxiv.org/abs/1603.09423

Synthetic Data for Text Localisation in Natural Images

• intro: CVPR 2016
• project page: http://www.robots.ox.ac.uk/~vgg/data/scenetext/
• arxiv: http://arxiv.org/abs/1604.06646
• paper: http://www.robots.ox.ac.uk/~vgg/data/scenetext/gupta16.pdf
• github: https://github.com/ankush-me/SynthText

Scene Text Detection via Holistic, Multi-Channel Prediction

• arxiv: http://arxiv.org/abs/1606.09002

Detecting Text in Natural Image with Connectionist Text Proposal Network

• intro: ECCV 2016
• arxiv: http://arxiv.org/abs/1609.03605
• github(Caffe): https://github.com/tianzhi0549/CTPN
• demo: http://textdet.com/

TextBoxes: A Fast Text Detector with a Single Deep Neural Network

• intro: AAAI 2017
• arxiv: https://arxiv.org/abs/1611.06779
• github(Caffe): https://github.com/MhLiao/TextBoxes

Text Recognition

Sequence to sequence learning for unconstrained scene text recognition

• intro: master thesis
• arxiv: http://arxiv.org/abs/1607.06125

Drawing and Recognizing Chinese Characters with Recurrent Neural Network

• arxiv: https://arxiv.org/abs/1606.06539

Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition

• intro: correct rates: Dataset-CASIA 97.10% and Dataset-ICDAR 97.15%
• arxiv: https://arxiv.org/abs/1610.02616

Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Chinese Character Recognition

• arxiv: https://arxiv.org/abs/1610.04057

Breaking Captcha

Using deep learning to break a Captcha system

• intro: “Using Torch code to break simplecaptcha with 92% accuracy”
• blog: https://deepmlblog.wordpress.com/2016/01/03/how-to-break-a-captcha-system/
• github: https://github.com/arunpatala/captcha

Breaking reddit captcha with 96% accuracy

• blog: https://deepmlblog.wordpress.com/2016/01/05/breaking-reddit-captcha-with-96-accuracy/
• github: https://github.com/arunpatala/reddit.captcha

I’m not a human: Breaking the Google reCAPTCHA

• paper: https://www.blackhat.com/docs/asia-16/materials/asia-16-Sivakorn-Im-Not-a-Human-Breaking-the-Google-reCAPTCHA-wp.pdf

Neural Net CAPTCHA Cracker

• slides: http://www.cs.sjsu.edu/faculty/pollett/masters/Semesters/Spring15/geetika/CS298%20Slides%20-%20PDF
• github: https://github.com/bgeetika/Captcha-Decoder
• demo: http://cp-training.appspot.com/

Recurrent neural networks for decoding CAPTCHAS

• blog: https://deepmlblog.wordpress.com/2016/01/12/recurrent-neural-networks-for-decoding-captchas/
• demo: http://simplecaptcha.sourceforge.net/
• code: http://sourceforge.net/projects/simplecaptcha/

Reading irctc captchas with 95% accuracy using deep learning

• github: https://github.com/arunpatala/captcha.irctc

端到端的OCR：基于CNN的实现

• blog: http://blog.xlvector.net/2016-05/mxnet-ocr-cnn/

I Am Robot: (Deep) Learning to Break Semantic Image CAPTCHAs

• intro: automatically solving 70.78% of the image reCaptchachallenges, while requiring only 19 seconds per challenge. apply to the Facebook image captcha and achieve an accuracy of 83.5%
• paper: http://www.cs.columbia.edu/~polakis/papers/sivakorn_eurosp16.pdf

Handwritten Recognition

High Performance Offline Handwritten Chinese Character Recognition Using GoogLeNet and Directional Feature Maps

• arxiv: http://arxiv.org/abs/1505.04925
• github: https://github.com/zhongzhuoyao/HCCR-GoogLeNet

Recognize your handwritten numbers

https://medium.com/@o.kroeger/recognize-your-handwritten-numbers-3f007cbe46ff#.jllz62xgu

Handwritten Digit Recognition using Convolutional Neural Networks in Python with Keras

• blog: http://machinelearningmastery.com/handwritten-digit-recognition-using-convolutional-neural-networks-python-keras/

MNIST Handwritten Digit Classifier

• github: https://github.com/karandesai-96/digit-classifier

如何用卷积神经网络CNN识别手写数字集？

• blog: http://www.cnblogs.com/charlotte77/p/5671136.html

LeNet – Convolutional Neural Network in Python

• blog: http://www.pyimagesearch.com/2016/08/01/lenet-convolutional-neural-network-in-python/

Scan, Attend and Read: End-to-End Handwritten Paragraph Recognition with MDLSTM Attention

• arxiv: http://arxiv.org/abs/1604.03286

MLPaint: the Real-Time Handwritten Digit Recognizer

• blog: http://blog.mldb.ai/blog/posts/2016/09/mlpaint/
• github: https://github.com/mldbai/mlpaint
• demo: https://docs.mldb.ai/ipy/notebooks/_demos/_latest/Image%20Processing%20with%20Convolutions.html

Training a Computer to Recognize Your Handwriting

https://medium.com/@annalyzin/training-a-computer-to-recognize-your-handwriting-24b808fb584#.gd4pb9jk2

Using TensorFlow to create your own handwriting recognition engine

• blog: https://niektemme.com/2016/02/21/tensorflow-handwriting/
• github: https://github.com/niektemme/tensorflow-mnist-predict/

Building a Deep Handwritten Digits Classifier using Microsoft Cognitive Toolkit

• blog: https://medium.com/@tuzzer/building-a-deep-handwritten-digits-classifier-using-microsoft-cognitive-toolkit-6ae966caec69#.c3h6o7oxf
• github: https://github.com/tuzzer/ai-gym/blob/a97936619cf56b5ed43329c6fa13f7e26b1d46b8/MNIST/minist_softmax_cntk.py

Plate Recognition

Reading Car License Plates Using Deep Convolutional Neural Networks and LSTMs

• arxiv: http://arxiv.org/abs/1601.05610

Number plate recognition with Tensorflow

• blog: http://matthewearl.github.io/2016/05/06/cnn-anpr/
• github(Deep ANPR): https://github.com/matthewearl/deep-anpr

end-to-end-for-plate-recognition

• github: https://github.com/szad670401/end-to-end-for-chinese-plate-recognition

Blogs

Applying OCR Technology for Receipt Recognition

• blog: http://rnd.azoft.com/applying-ocr-technology-receipt-recognition/
• mirror: http://pan.baidu.com/s/1qXQBQiC

Hacking MNIST in 30 lines of Python

• blog: http://jrusev.github.io/post/hacking-mnist/
• github: https://github.com/jrusev/simple-neural-networks

Projects

ocropy: Python-based tools for document analysis and OCR

• github: https://github.com/tmbdev/ocropy

Extracting text from an image using Ocropus

• blog: http://www.danvk.org/2015/01/09/extracting-text-from-an-image-using-ocropus.html

CLSTM : A small C++ implementation of LSTM networks, focused on OCR

• github: https://github.com/tmbdev/clstm

caffe-ocr: OCR with caffe deep learning framework

• github: https://github.com/pannous/caffe-ocr

Digit Recognition via CNN: digital meter numbers detection

• github(caffe): https://github.com/SHUCV/digit

Attention-OCR: Visual Attention based OCR

• github: https://github.com/da03/Attention-OCR

umaru: An OCR-system based on torch using the technique of LSTM/GRU-RNN, CTC and referred to the works of rnnlib and clstm

• github: https://github.com/edward-zhu/umaru

Tesseract.js: Pure Javascript OCR for 62 Languages

• homepage: http://tesseract.projectnaptha.com/
• github: https://github.com/naptha/tesseract.js

DeepHCCR: Offline Handwritten Chinese Character Recognition based on GoogLeNet and AlexNet (With CaffeModel)

• github: https://github.com/chongyangtao/DeepHCCR

Datasets

COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images

• homepage: http://vision.cornell.edu/se3/coco-text/
• arxiv: http://arxiv.org/abs/1601.07140

Videos

LSTMs for OCR

• youtube: https://www.youtube.com/watch?v=5vW8faXvnrc

Resources

Scene Text Localization & Recognition Resources

• intro: A curated list of resources dedicated to scene text localization and recognition
• github: https://github.com/chongyangtao/Awesome-Scene-Text-Recognition