OCR 2016

2016

• Yin X C, Zuo Z Y, Tian S, et al. Text detection, tracking and recognition in video: a comprehensive survey[J]. IEEE Transactions on Image Processing, 2016, 25(6): 2752-2773.
• Zhu Y, Yao C, Bai X. Scene text detection and recognition: Recent advances and future trends[J]. Frontiers of Computer Science, 2016, 10(1): 19-36.
• He P, Huang W, Qiao Y, et al. Reading Scene Text in Deep Convolutional Sequences[C]//AAAI. 2016: 3501-3508.
  
        code:[code]
• Lee C Y, Osindero S. Recursive recurrent nets with attention modeling for OCR in the wild[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016: 2231-2239.
• 【Synthetic data】Gupta A, Vedaldi A, Zisserman A. Synthetic data for text localisation in natural images[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016: 2315-2324.
  
        code:[offical;vgg;other]
• Sivakorn S, Polakis J, Keromytis A D. I’m not a human: Breaking the Google reCAPTCHA[J]. Black Hat,(i), 2016: 1-12.
• Sivakorn S, Polakis I, Keromytis A D. I am robot:(deep) learning to break semantic image captchas[C]//Security and Privacy (EuroS&P), 2016 IEEE European Symposium on. IEEE, 2016: 388-403.
• Lee C Y, Osindero S. Recursive recurrent nets with attention modeling for OCR in the wild[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016: 2231-2239.
• Neumann L, Matas J. Real-time lexicon-free scene text localization and recognition[J]. IEEE transactions on pattern analysis and machine intelligence, 2016, 38(9): 1872-1885.
• Zhang Z, Zhang C, Shen W, et al. Multi-oriented text detection with fully convolutional networks[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016: 4159-4167.
• Fabrizio J, Robert-Seidowsky M, Dubuisson S, et al. TextCatcher: a method to detect curved and challenging text in natural scenes[J]. International Journal on Document Analysis and Recognition (IJDAR), 2016, 19(2): 99-117.
• Cho H, Sung M, Jun B. Canny text detector: Fast and robust scene text localization algorithm[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016: 3566-3573.
• Qiang G, Dan T, Guohui L, et al. Memory Matters: Convolutional Recurrent Neural Network for Scene Text Recognition[J]. arXiv preprint arXiv:1601.01100, 2016.
• Mishra A, Alahari K, Jawahar C V. Enhancing energy minimization framework for scene text recognition with top-down cues[J]. Computer Vision and Image Understanding, 2016, 145: 30-42.
• Li H, Shen C. Reading car license plates using deep convolutional neural networks and lstms[J]. arXiv preprint arXiv:1601.05610, 2016.
• Veit A, Matera T, Neumann L, et al. Coco-text: Dataset and benchmark for text detection and recognition in natural images[J]. arXiv preprint arXiv:1601.07140, 2016.
• Huang W. Context modeling for semantic text matching and scene text detection[M]. The Pennsylvania State University, 2016.
• Tian S, Pei W Y, Zuo Z Y, et al. Scene Text Detection in Video by Learning Locally and Globally[C]//IJCAI. 2016: 2647-2653.
• Shi B, Wang X, Lyu P, et al. Robust scene text recognition with automatic rectification[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016: 4168-4176.
• Shuye Zhang, Mude Lin, Tianshui Chen, Lianwen Jin, Liang Lin. Character Proposal Network for Robust Text Extraction. arXiv preprint arXiv:1602.04348, 2016.
• Lluis Gomez, Dimosthenis Karatzas. A fine-grained approach to scene text script identification. arXiv preprint arXiv:1602.07475, 2016.
• Lluis Gomez, Anguelos Nicolaou, Dimosthenis Karatzas. Improving patch-based scene text script identification with ensembles of conjoined networks. arXiv preprint arXiv:1602.07480, 2016.
• He T, Huang W, Qiao Y, et al. Accurate text localization in natural image with cascaded convolutional text network[J]. arXiv preprint arXiv:1603.09423, 2016.
• Hafemann L G, Sabourin R, Oliveira L S. Writer-independent feature learning for offline signature verification using deep convolutional neural networks[C]//Neural Networks (IJCNN), 2016 International Joint Conference on. IEEE, 2016: 2576-2583.
• Ren X, Chen K, Sun J. A CNN Based Scene Chinese Text Recognition Algorithm With Synthetic Data Engine[J]. arXiv preprint arXiv:1604.01891, 2016.
• Xiaohang Ren, Kai Chen, Jun Sun. A Novel Scene Text Detection Algorithm Based On Convolutional Neural Network. arXiv preprint arXiv:1604.01894, 2016.
• Gómez L, Karatzas D. Textproposals: a text-specific selective search algorithm for word spotting in the wild[J]. Pattern Recognition, 2017, 70: 60-74.[code]
• Bluche T, Louradour J, Messina R. Scan, attend and read: End-to-end handwritten paragraph recognition with mdlstm attention[J]. arXiv preprint arXiv:1604.03286, 2016.
• Zheng Zhang, Chengquan Zhang, Wei Shen, Cong Yao, Wenyu Liu, Xiang Bai. Multi-Oriented Text Detection with Fully Convolutional Networks. arXiv preprint arXiv:1604.04018, 2016.
• Xie Z, Sun Z, Jin L, et al. Fully convolutional recurrent network for handwritten Chinese text recognition[C]//Pattern Recognition (ICPR), 2016 23rd International Conference on. IEEE, 2016: 4011-4016.
• Shangxuan Tian, Yifeng Pan, Chang Huang, Shijian Lu, Kai Yu, Chew Lim Tan. Text Flow: A Unified Text Detection System in Natural Scene Images. arXiv preprint arXiv:1604.06877, 2016.
• Zhong Z, Jin L, Zhang S, et al. Deeptext: A unified framework for text proposal generation and text detection in natural images[J]. arXiv preprint arXiv:1605.07314, 2016.
• Zhang X Y, Yin F, Zhang Y M, et al. Drawing and recognizing chinese characters with recurrent neural network[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017.
• Yao C, Bai X, Sang N, et al. Scene text detection via holistic, multi-channel prediction[J]. arXiv preprint arXiv:1606.09002, 2016.
• Hassanien A M A. Sequence to sequence learning for unconstrained scene text recognition[J]. arXiv preprint arXiv:1607.06125, 2016.
• Nitigya Sambyal, Pawanesh Abrol. Automatic text extraction and character segmentation using maximally stable extremal regions. arXiv preprint arXiv:1608.03374, 2016.
• 【Synthetic data】 Krishnan P, Jawahar C V. Generating Synthetic Data for Text Recognition[J]. arXiv preprint arXiv:1608.04224, 2016.
• 【CTPN】Tian Z, Huang W, He T, et al. Detecting text in natural image with connectionist text proposal network[C]//European Conference on Computer Vision. Springer International Publishing, 2016: 56-72.
  
          code:[code;cuda8-caffe;offical;ocr_detection_ctpn;keras_ocr]
  
       dataset:[ICDAR 2011; ICDAR 2013; ICDAR 2015; SWT; Multilingual dataset]
• Xie Z, Sun Z, Jin L, et al. Learning spatial-semantic context with fully convolutional recurrent network for online handwritten chinese text recognition[J]. IEEE transactions on pattern analysis and machine intelligence, 2017.
• Hu B, Liu X, Wu X, et al. Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Chinese Character Recognition[J]. arXiv preprint arXiv:1610.04057, 2016.
• Ahmed Ibrahim, A. Lynn Abbott, Mohamed E. Hussein. An Image Dataset of Text Patches in Everyday Scenes. arXiv preprint arXiv:1610.06494, 2016.
• Lou X, Kansky K, Lehrach W, et al. Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data[C]//Advances in Neural Information Processing Systems. 2016: 2793-2801.
• Xu Y, Shan S, Qiu Z, et al. End-to-End Subtitle Detection and Recognition for Videos in East Asian Languages via CNN Ensemble with Near-Human-Level Performance[J]. arXiv preprint arXiv:1611.06159, 2016.
• Chengzhe Yan, Jie Hu, Changshui Zhang. A DNN Framework For Text Image Rectification From Planar Transformations. arXiv preprint arXiv:1611.04298, 2016.
• Minghui Liao, Baoguang Shi, Xiang Bai, Xinggang Wang, Wenyu Liu. TextBoxes: A Fast Text Detector with a Single Deep Neural Network. arXiv preprint arXiv:1611.06779, 2016.
• Jie Mei, Aminul Islam, Yajing Wu, Abidalrahman Moh’d, Evangelos E. Milios. Statistical Learning for OCR Text Correction. arXiv preprint arXiv:1611.06950, 2016.
• Yang X, He D, Huang W, et al. Smart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Reading[J]. arXiv preprint arXiv:1611.07385, 2016.
• Junnan Yu, Xuna Ma, Ting Han. Usability Investigation on the Localization of Text CAPTCHAs: Take Chinese Characters as a Case Study. arXiv preprint arXiv:1612.01070, 2016.
• Singh Vijendra, Nisha Vasudeva, Hem Jyotsana Parashar. Recognition of Text Image Using Multilayer Perceptron. arXiv preprint arXiv:1612.00625, 2016.
• Zichuan Liu, Yixing Li, Fengbo Ren, Hao Yu. A Binary Convolutional Encoder-decoder Network for Real-time Natural Scene Text Processing. arXiv preprint arXiv:1612.03630, 2016.

来源：CSDN

作者：DrogoZhang

链接：https://blog.csdn.net/weixin_40400177/article/details/103541021