原文链接： http://blog.csdn.net/PeaceInMind/article/details/51387367
[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]
[2018-CVPR]Rotation-Sensitive Regression for Oriented Scene Text Detection[paper]
[2018-CVPR] Single Shot Text Spotter with Explicit Alignment and Attention[paper]
[2018-CVPR] Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation [paper]
[2018-arxiv]TextBoxes++: A Single-Shot Oriented Scene Text Detector[paper][code]
[2018-arxiv]FOTS: Fast OrientedText Spotting with a Unified Network[paper]
[2018-AAAI] PixelLink: Detecting Scene 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-ICCV]Single Shot Text Detector with Regional Attention[pdf]
[2017-ICCV]WordSup: Exploiting Word Annotations for Character based Text Detection[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]
[2017-arXiv]AdaDNNs: Adaptive Ensemble of Deep Neural Networks for Scene Text Recognition [paper]
[2017-arXiv]STN-OCR: A single Neural Network for Text Detection and Text Recognition[paper][code]
[2017-arXiv]Auto-Encoder Guided GAN for Chinese Calligraphy Synthesis[paper]
[2017-AAAI-网络图片]Detection and Recognition of Text Embedded in Online Images via Neural Context Models[paper][project]
[2017-arvix 文档识别] Full-Page Text Recognition : Learning Where to Start and When to Stop[paper]
[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]
Total-Text 2017
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-Words 2012
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 Database 2010
3000images of indoor and outdoor scenes containing text
Korean,English (Number), and Mixed (Korean + English + Number)
Task:text location, segmentation and recognition
Chars74k 2009
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
Dataset
Discription
Competition Paper
ICDAR 2015
1000 training images and 500 testing images
paper
ICDAR 2013
229 training images and 233 testing images
paper
ICDAR 2011
229 training images and 255 testing images
paper
ICDAR 2005
1001 training images and 489 testing images
paper
ICDAR 2003
181 training images and 251 testing images(word level and character level)
paper
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]
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]
[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)
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]
[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]
[1]http://handong1587.github.io/deep_learning/2015/10/09/ocr.html
[2]ttps://github.com/chongyangtao/Awesome-Scene-Text-Recognition
