Awesome-Mirrors/awesome-deep-text-detection-recognition
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@ -81,7 +81,7 @@ A curated list of awesome deep learning based papers on text detection and recog
'15-ICLR | 14/12/18 | [Deep structured output learning for unconstrained text recognition](https://arxiv.org/pdf/1412.5903.pdf) | 0.717 | |0.896 | 0.818 | [`TF`](https://github.com/AlexandreSev/Structured_Data) <br> [`SLIDE`](https://www.robots.ox.ac.uk/~vgg/publications/2015/Jaderberg15a/presentation.pdf) <br> [`VIDEO`](https://www.youtube.com/watch?v=NYkG38RCoRg) '15-ICLR | 14/12/18 | [Deep structured output learning for unconstrained text recognition](https://arxiv.org/pdf/1412.5903.pdf) | 0.717 | |0.896 | 0.818 | [`TF`](https://github.com/AlexandreSev/Structured_Data) <br> [`SLIDE`](https://www.robots.ox.ac.uk/~vgg/publications/2015/Jaderberg15a/presentation.pdf) <br> [`VIDEO`](https://www.youtube.com/watch?v=NYkG38RCoRg)
'16-IJCV | 15/05/07 | [Reading text in the wild with convolutional neural networks](https://arxiv.org/pdf/1412.1842.pdf) | 0.807 | | 0.933 | 0.908 | [`KERAS`](https://github.com/mathDR/reading-text-in-the-wild) '16-IJCV | 15/05/07 | [Reading text in the wild with convolutional neural networks](https://arxiv.org/pdf/1412.1842.pdf) | 0.807 | | 0.933 | 0.908 | [`KERAS`](https://github.com/mathDR/reading-text-in-the-wild)
'16-AAAI | 15/06/14 | [Reading Scene Text in Deep Convolutional Sequences](https://arxiv.org/pdf/1506.04395.pdf) '16-AAAI | 15/06/14 | [Reading Scene Text in Deep Convolutional Sequences](https://arxiv.org/pdf/1506.04395.pdf)
'17-TPAMI | 15/07/21 | [An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition](https://arxiv.org/pdf/1507.05717.pdf) | 0.808 | 0.782 | 0.894 | 0.867 | [`TORCH(M)`](https://github.com/bgshih/crnn) <br> [`TF`](https://github.com/weinman/cnn_lstm_ctc_ocr) <br> [`TF`](https://github.com/watsonyanghx/CNN_LSTM_CTC_Tensorflow) <br> [`TF`](https://github.com/MaybeShewill-CV/CRNN_Tensorflow) <br> [`PYTORCH`](https://github.com/meijieru/crnn.pytorch) <br> [`BLOG(KR)`](https://medium.com/@mldevhong/%EB%85%BC%EB%AC%B8-%EB%B2%88%EC%97%AD-rcnn-an-end-to-end-trainable-neural-network-for-image-based-sequence-recognition-and-its-f6456886d6f8) '17-TPAMI | 15/07/21 | [An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition](https://arxiv.org/pdf/1507.05717.pdf) | 0.808 | 0.782 | 0.894 | 0.867 | [`TORCH(M)`](https://github.com/bgshih/crnn) <br> [`TF`](https://github.com/weinman/cnn_lstm_ctc_ocr) <br> [`TF`](https://github.com/watsonyanghx/CNN_LSTM_CTC_Tensorflow) <br> [`TF`](https://github.com/MaybeShewill-CV/CRNN_Tensorflow) <br> [`TF`](https://github.com/bai-shang/OCR_TF_CRNN_CTC) <br> [`PYTORCH`](https://github.com/meijieru/crnn.pytorch) <br> [`BLOG(KR)`](https://medium.com/@mldevhong/%EB%85%BC%EB%AC%B8-%EB%B2%88%EC%97%AD-rcnn-an-end-to-end-trainable-neural-network-for-image-based-sequence-recognition-and-its-f6456886d6f8)
'16-CVPR | 16/03/09 | [Recursive Recurrent Nets with Attention Modeling for OCR in the Wild](https://arxiv.org/pdf/1603.03101.pdf) | 0.807 | 0.784 | 0.887 | 0.9 | '16-CVPR | 16/03/09 | [Recursive Recurrent Nets with Attention Modeling for OCR in the Wild](https://arxiv.org/pdf/1603.03101.pdf) | 0.807 | 0.784 | 0.887 | 0.9 |
'16-CVPR | 16/03/12 | [Robust scene text recognition with automatic rectification](https://arxiv.org/pdf/1603.03915.pdf) | 0.819 | 0.819 | 0.901 | 0.886 | [`PYTORCH`](https://github.com/marvis/ocr_attention) <br> [`PYTORCH`](https://github.com/WarBean/tps_stn_pytorch) '16-CVPR | 16/03/12 | [Robust scene text recognition with automatic rectification](https://arxiv.org/pdf/1603.03915.pdf) | 0.819 | 0.819 | 0.901 | 0.886 | [`PYTORCH`](https://github.com/marvis/ocr_attention) <br> [`PYTORCH`](https://github.com/WarBean/tps_stn_pytorch)
'16-CVPR | 16/06/27 | [CNN-N-Gram for Handwriting Word Recognition](https://www.cs.tau.ac.il/~wolf/papers/CNNNGram.pdf) | 0.8362 | | | | [`VIDEO`](https://www.youtube.com/watch?v=czc2Ipm3Bis) '16-CVPR | 16/06/27 | [CNN-N-Gram for Handwriting Word Recognition](https://www.cs.tau.ac.il/~wolf/papers/CNNNGram.pdf) | 0.8362 | | | | [`VIDEO`](https://www.youtube.com/watch?v=czc2Ipm3Bis)