Papers › SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition
SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition
Zhi Qiao, Yu Zhou, Dongbao Yang, Yucan Zhou, Weiping Wang
Scene text recognition is a hot research topic in computer vision. Recently, many recognition methods based on the encoder-decoder framework have been proposed, and they can handle scene texts of perspective distortion and curve shape. Nevertheless, they still face lots of challenges like image blur, uneven illumination, and incomplete characters. We argue that most encoder-decoder methods are based on local visual features without explicit global semantic information. In this work, we propose a semantics enhanced encoder-decoder framework to robustly recognize low-quality scene texts. The semantic information is used both in the encoder module for supervision and in the decoder module for initializing. In particular, the state-of-the art ASTER method is integrated into the proposed framework as an exemplar. Extensive experiments demonstrate that the proposed framework is more robust for low-quality text images, and achieves state-of-the-art results on several benchmark datasets.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Optical Character Recognition (OCR) | Benchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical Study | SEED | Accuracy (%) | 61.2 | #7 of 7 | Archive leaderboard | report |
| Scene Text Recognition | ICDAR2013 | SEED | Accuracy | 92.8 | #28 of 38 | Archive leaderboard | report |
| Scene Text Recognition | ICDAR2015 | SEED | Accuracy | 80 | #18 of 27 | Archive leaderboard | report |
| Scene Text Recognition | SVT | SEED | Accuracy | 89.6 | #26 of 37 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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