The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition
Open accessAbstract
Recognizing irregular text in natural scene images is challenging due to the large variance in text appearance, such as curvature, orientation and distortion. Most existing approaches rely heavily on sophisticated model designs and/or extra fine-grained annotations, which, to some extent, increase the difficulty in algorithm implementation and data collection. In this work, we propose an easy-to-implement strong baseline for irregular scene text recognition, using offthe-shelf neural network components and only word-level annotations. It is composed of a 31-layer ResNet, an LSTMbased encoder-decoder framework and a 2-dimensional attention module. Despite its simplicity, the proposed method is robust. It achieves state-of-the-art performance on irregular text recognition benchmarks and comparable results on regular text datasets. The code will be released.
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Cites
Deep Residual Learning for Image Recognition
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Adam: A Method for Stochastic Optimization
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Sequence to Sequence Learning with Neural Networks
Sutskever, I., Vinyals, O., & Le, Q. V. (2014) · arXiv · doi:10.48550/arxiv.1409.3215 · Cited by 17,766
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
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Shi, B., Bai, X., & Yao, C. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2646371 · Cited by 3,172
NewsWeeder: Learning to Filter Netnews
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Attention-Based Models for Speech Recognition
Chorowski, J., Bahdanau, D., Serdyuk, D., Cho, K., & Bengio, Y. (2015) · arXiv · doi:10.48550/arxiv.1506.07503 · Cited by 2,021
Synthetic Data for Text Localisation in Natural Images
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ICDAR 2013 Robust Reading Competition
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Reading text in the wild with convolutional neural networks
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Cited by
Attention, please! A survey of neural attention models in deep learning
de Santana Correia, A., & Colombini, E. L. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10148-x · Cited by 298
Text Recognition in the Wild: A Survey
Chen, X., Jin, L., Zhu, Y., Luo, C., & Wang, T. (2022) · ACM Computing Surveys · doi:10.1145/3440756 · Cited by 205
PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text
Wang, W., Xie, E., Li, X., Liu, X., Liang, D., Zhibo, Y., Lu, T., & Shen, C. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3077555 · Cited by 140
Self-citation
Metadata
- Authors
- Li, H., Wang, P., Shen, C., & Zhang, G.
- Venue
- Proceedings of the AAAI Conference on Artificial Intelligence
- Published
- 2019-07-17
- Volume
- 33
- Issue
- 01
- Pages
- 8610-8617
- ISSN
- 2159-5399 (ISSN-L)
- 2374-3468
- OpenAlex
- W2965066169
- Cited by
- 432
- References
- 30
- FWCI
- 17.12
- Type
- conference paper
- Language
- en
- Open access
- diamond
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- Li, H., Wang, P., Shen, C., & Zhang, G. (2019). Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition. Proceedings of the AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v33i01.33018610
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