[2015-PAMI-Overview]Text Detection and Recognition in Imagery: A Survey[paper]

[2014-Front.Comput.Sci-Overview]Scene Text Detection and Recognition: Recent Advances and Future Trends[paper]

自然场景文字检测

[2018-arxiv]TextBoxes++: ASingle-Shot Oriented Scene Text Detector[paper]

[2018-arxiv]FOTS: Fast OrientedText Spotting with a Unified Network[paper]

[2018-AAAI] PixelLink: DetectingScene Text via Instance Segmentation[paper]

[2017-arXiv]Fused Text Segmentation Networks for Multi-oriented Scene Text Detection[paper]

[2017-arXiv]WeText: Scene Text Detection under Weak Supervision[paper]

[2017-arXiv]R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection[paper]

[2017-CVPR]EAST: An Efficient and Accurate Scene Text Detector [paper][code]

[2017-arXiv]Cascaded Segmentation-Detection Networks for Word-Level Text Spotting[paper]

[2017-arXiv]Deep Direct Regression for Multi-Oriented Scene Text Detection[paper]

[2017-CVPR]Detecting oriented text in natural images by linking segments [paper][code]

[2017-CVPR]Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection[paper]

[2017-arXiv]Arbitrary-Oriented Scene Text Detection via Rotation Proposals [paper]

[2017-AAAI]TextBoxes: A Fast Text Detector with a Single Deep Neural Network[paper][code]

[2016-arXiv]Accurate Text Localization in Natural Image with Cascaded Convolutional TextNetwork [paper]

[2016-arXiv]DeepText : A Unified Framework for Text Proposal Generation and Text Detectionin Natural Images [paper] [data]

[2017-PR]TextProposals: a Text-specific Selective Search Algorithm for Word Spotting in the Wild [paper] [code]

[2016-arXiv] SceneText Detection via Holistic, Multi-Channel Prediction [paper]

[2016-CVPR] CannyText Detector: Fast and Robust Scene Text Localization Algorithm [paper]

[2016-CVPR]Synthetic Data for Text Localisation in Natural Images [paper] [data][code]

[2016-ECCV]Detecting Text in Natural Image with Connectionist Text Proposal Network[paper][demo][code]

[2016-TIP]Text-Attentional Convolutional Neural Networks for Scene Text Detection [paper]

[2016-IJDAR]TextCatcher: a method to detect curved and challenging text in natural scenes[paper]

[2016-CVPR]Multi-oriented text detection with fully convolutional networks [paper]

[2015-TPRMI]Real-time Lexicon-free Scene Text Localization and Recognition[paper]

[2015-CVPR]Symmetry-Based Text Line Detection in Natural Scenes[paper][code]

[2015-ICCV]FASText: Efficient unconstrained scene text detector[paper][code]

[2015-D.PhilThesis] Deep Learning for Text Spotting [paper]

[2015 ICDAR]Object Proposals for Text Extraction in the Wild [paper] [code]

[2014-ECCV] Deep Features for Text Spotting [paper] [code] [model] [GitXiv]

[2014-TPAMI] Word Spotting and Recognition with Embedded Attributes [paper] [homepage] [code]

[2014-TPRMI]Robust Text Detection in Natural Scene Images[paper]

[2014-ECCV] Robust Scene Text Detection with Convolution Neural Network Induced MSER Trees [paper]

[2013-ICCV] Photo OCR: Reading Text in Uncontrolled Conditions[paper]

[2012-CVPR]Real-time scene text localization and recognition[paper][code]

[2010-CVPR]Detecting Text in Natural Scenes with Stroke Width Transform [paper] [code]

自然场景文字识别

[2016-AAAI]Reading Scene Text in Deep Convolutional Sequences [paper]

[2016-IJCV]Reading Text in the Wild with Convolutional Neural Networks [paper] [demo] [homepage]

[2016-CVPR]Recursive Recurrent Nets with Attention Modeling for OCR in the Wild [paper]

[2016-CVPR] Robust Scene Text Recognition with Automatic Rectification [paper]

[2016-NIPs] Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data[paper]

[2015-CoRR] AnEnd-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition [paper] [code]

[2015-ICDAR]Automatic Script Identification in the Wild[paper]

[2015-ICLR] Deep structured output learning for unconstrained text recognition [paper]

[2014-NIPS]Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition [paperhomepage] [model]

[2014-TIP] A Unified Framework for Multi-Oriented Text Detection and Recognition [paper]

[2012-ICPR]End-to-End Text Recognition with Convolutional Neural Networks [paper] [code] [SVHN Dataset]

数据集

Total-Text2017

1555 images,11459 text instances, includes curved text

COCO-Text (ComputerVision Group, Cornell)2016

63,686images, 173,589 text instances, 3 fine-grained text attributes.

Task:text location and recognition

COCO-Text API

Synthetic Data for Text Localisation in Natural Image (VGG)2016

800k thousand images

8 million synthetic word instances

download

Synthetic Word Dataset (Oxford, VGG)2014

9million images covering 90k English words

Task:text recognition, segmentation

download

IIIT 5K-Words2012

5000images from Scene Texts and born-digital (2k training and 3k testing images)

Eachimage is a cropped word image of scene text with case-insensitive labels

Task:text recognition

download

StanfordSynth(Stanford, AI Group)2012

Smallsingle-character images of 62 characters (0-9, a-z, A-Z)

Task:text recognition

download

MSRA Text Detection 500 Database(MSRA-TD500)2012

500 natural images(resolutions of the images vary from 1296x864 to 1920x1280)

Chinese,English or mixture of both

Task:text detection

Street View Text (SVT)2010

350 high resolution images (average size 1260 × 860) (100 images for training and 250 images for testing)

Onlyword level bounding boxes are provided with case-insensitive labels

Task:text location

KAIST Scene_Text Database2010

3000images of indoor and outdoor scenes containing text

Korean,English (Number), and Mixed (Korean + English + Number)

Task:text location, segmentation and recognition

Chars74k2009

Over74K images from natural images, as well as a set of synthetically generatedcharacters

Smallsingle-character images of 62 characters (0-9, a-z, A-Z)

Task:text recognition

ICDARBenchmark Datasets

开源库

Tesseract: c++ based tools for documents analysis and OCR,support 60+ languages [code]

Ocropy: Python-based tools for document analysis and OCR [code]

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

Convolutional Recurrent Neural Network,Torch7 based [code]

Attention-OCR: Visual Attention based OCR [code]

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

其他

DeepFont:Identify Your Font from An Image[paper]

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

End-to-End Interpretation of the French Street Name Signs Dataset [paper] [code]

Extracting text from an image using Ocropus [blog]

手写字识别

[2016-arXiv]Drawingand Recognizing Chinese Characters with Recurrent Neural Network [paper]

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

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

High Performance Offline Handwritten Chinese Character Recognition Using GoogLeNet and Directional Feature Maps [paper] [github]

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

如何用卷积神经网络CNN识别手写数字集？[blog][blog1][blog2] [blog4] [blog5] [code6]

Scan,Attend and Read: End-to-End Handwritten Paragraph Recognition with MDLSTMAttention [paper]

MLPaint:the Real-Time Handwritten Digit Recognizer [blog][code][demo]

caffe-ocr: OCR with caffe deep learning framework [code] (单字分类器)

牌照等识别

ReadingCar License Plates Using Deep Convolutional Neural Networks and LSTMs  [paper]

Numberplate recognition with Tensorflow [blog] [code]

end-to-end-for-plate-recognition[code]

ApplyingOCR Technology for Receipt Recognition[blog][mirror]

破解验证码

[2017-Arvix]Using Synthetic Data to Train NeuralNetworks is Model-Based Reasoning[paper]

Using deep learning to break a Captcha system [blog] [code]

Breakingreddit captcha with 96% accuracy [blog] [code]

I'mnot a human: Breaking the Google reCAPTCHA [paper]

NeuralNet CAPTCHA Cracker [slides] [code] [demo]

Recurrentneural networks for decoding CAPTCHAS [blog] [code] [demo]

Readingirctc captchas with 95% accuracy using deep learning [code]

端到端的OCR：基于CNN的实现[blog]

IAm Robot: (Deep) Learning to Break Semantic Image CAPTCHAs [paper]

参考

[1]http://handong1587.github.io/deep_learning/2015/10/09/ocr.html

[2]https://github.com/chongyangtao/Awesome-Scene-Text-Recognition