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68 lines
4.5 KiB
Markdown
68 lines
4.5 KiB
Markdown
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# Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition
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## Introduction
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[ALGORITHM]
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```bibtex
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@inproceedings{li2019show,
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title={Show, attend and read: A simple and strong baseline for irregular text recognition},
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author={Li, Hui and Wang, Peng and Shen, Chunhua and Zhang, Guyu},
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booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
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volume={33},
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number={01},
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pages={8610--8617},
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year={2019}
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}
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```
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## Dataset
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### Train Dataset
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| trainset | instance_num | repeat_num | source |
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| :--------: | :----------: | :--------: | :----------------------: |
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| icdar_2011 | 3567 | 20 | real |
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| icdar_2013 | 848 | 20 | real |
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| icdar2015 | 4468 | 20 | real |
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| coco_text | 42142 | 20 | real |
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| IIIT5K | 2000 | 20 | real |
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| SynthText | 2400000 | 1 | synth |
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| SynthAdd | 1216889 | 1 | synth, 1.6m in [[1]](#1) |
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| Syn90k | 2400000 | 1 | synth |
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### Test Dataset
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| testset | instance_num | type |
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| :-----: | :----------: | :-------------------------: |
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| IIIT5K | 3000 | regular |
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| SVT | 647 | regular |
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| IC13 | 1015 | regular |
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| IC15 | 2077 | irregular |
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| SVTP | 645 | irregular, 639 in [[1]](#1) |
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| CT80 | 288 | irregular |
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## Results and Models
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| Methods | Backbone | Decoder | | Regular Text | | | | Irregular Text | | download |
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| :-----------------------------------------------------------------: | :---------: | :------------------: | :----: | :----------: | :--: | :-: | :--: | :------------: | :--: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| | | | IIIT5K | SVT | IC13 | | IC15 | SVTP | CT80 |
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| [SAR](/configs/textrecog/sar/sar_r31_parallel_decoder_academic.py) | R31-1/8-1/4 | ParallelSARDecoder | 95.0 | 89.6 | 93.7 | | 79.0 | 82.2 | 88.9 | [model](https://download.openmmlab.com/mmocr/textrecog/sar/sar_r31_parallel_decoder_academic-dba3a4a3.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/sar/20210327_154129.log.json) |
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| [SAR](configs/textrecog/sar/sar_r31_sequential_decoder_academic.py) | R31-1/8-1/4 | SequentialSARDecoder | 95.2 | 88.7 | 92.4 | | 78.2 | 81.9 | 89.6 | [model](https://download.openmmlab.com/mmocr/textrecog/sar/sar_r31_sequential_decoder_academic-d06c9a8e.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/sar/20210330_105728.log.json) |
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**Notes:**
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- `R31-1/8-1/4` means the height of feature from backbone is 1/8 of input image, where 1/4 for width.
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- We did not use beam search during decoding.
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- We implemented two kinds of decoder. Namely, `ParallelSARDecoder` and `SequentialSARDecoder`.
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- `ParallelSARDecoder`: Parallel decoding during training with `LSTM` layer. It would be faster.
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- `SequentialSARDecoder`: Sequential Decoding during training with `LSTMCell`. It would be easier to understand.
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- For train dataset.
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- We did not construct distinct data groups (20 groups in [[1]](#1)) to train the model group-by-group since it would render model training too complicated.
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- Instead, we randomly selected `2.4m` patches from `Syn90k`, `2.4m` from `SynthText` and `1.2m` from `SynthAdd`, and grouped all data together. See [config](https://download.openmmlab.com/mmocr/textrecog/sar/sar_r31_academic.py) for details.
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- We used 48 GPUs with `total_batch_size = 64 * 48` in the experiment above to speedup training, while keeping the `initial lr = 1e-3` unchanged.
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## References
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<a id="1">[1]</a> Li, Hui and Wang, Peng and Shen, Chunhua and Zhang, Guyu. Show, attend and read: A simple and strong baseline for irregular text recognition. In AAAI 2019.
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