Handwriting Text
Handwriting text recognition (HTR)
Baoguang Shi, Xiang Bai, and Cong Yao. An endto- end trainable neural network for image-based sequence recognition and its application to scene text recognition. IEEE transactions on pattern analysis and machine intelligence, 39(11):2298–2304, 2016. -> using convolutional recurrent neural network (CRNN) architecture for scene text recognition
Arik Poznanski and Lior Wolf. Cnn-n-gram for handwriting word recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 2305–2314, 2016. -> using an RCNN to estimate an n-gram profile of an image and match it to the profile of an existing word from a dictionary
Sebastian Sudholt and Gernot A Fink. Phocnet: A deep convolutional neural network for word spotting in handwritten documents. In 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), pages 277–282. IEEE, 2016. -> improves the architecture from Poznanski et al 2016
Jorge Sueiras, Victoria Ruiz, Angel Sanchez, and Jose F Velez. Offline continuous handwriting recognition using sequence to sequence neural networks. Neurocomputing, 289:119–128, 2018. -> use attention decoder instead of RCNN outputs
Kartik Dutta, Praveen Krishnan, Minesh Mathew, and CV Jawahar. Improving cnn-rnn hybrid networks for handwriting recognition. In 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), pages 80–85. IEEE, 2018. -> they mix several strategies developed in previous years into one architecture
Handwriting text generation (HTG)
Alex Graves. Generating sequences with recurrent neural networks. arXiv preprint arXiv:1308.0850 2013. -> LSTM for generating text sequences
Bo Ji and Tianyi Chen. Generative adversarial network for handwritten text. arXiv:1907.11845, 2019 -> extends Graves 2013 with a Discriminator and converts it into a GAN paradigm
Emre Aksan, Fabrizio Pece, and Otmar Hilliges. Deepwriting: Making digital ink editable via deep generative modeling. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pages 1–14 2018. -> aka DeepWriting; introduces control of the styling for Graves 2013.
Eloi Alonso, Bastien Moysset, and Ronaldo Messina. Adversarial generation of handwritten text images conditioned on sequences. arXiv preprint arXiv:1903.00277, 2019 -> generate text images conditioned on input text; for this, they extend a BigGAN architecture (Brock et al. 2018); the generator can produce images of fied size but containing text of variable length
Sharon Fogel, Hadar Averbuch-Elor, Sarel Cohen, Shai Mazor, Roee Litman. ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation. arXiv:2003.10557, 2020 -> build upon Alonso et al 2019 to produce a network that generates images with both variable text length and variable image size.
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