Papers › Syntax-Aware Network for Handwritten Mathematical Expression Recognition
Syntax-Aware Network for Handwritten Mathematical Expression Recognition
Ye Yuan, Xiao Liu, Wondimu Dikubab, Hui Liu, Zhilong Ji, Zhongqin Wu, Xiang Bai
Handwritten mathematical expression recognition (HMER) is a challenging task that has many potential applications. Recent methods for HMER have achieved outstanding performance with an encoder-decoder architecture. However, these methods adhere to the paradigm that the prediction is made "from one character to another", which inevitably yields prediction errors due to the complicated structures of mathematical expressions or crabbed handwritings. In this paper, we propose a simple and efficient method for HMER, which is the first to incorporate syntax information into an encoder-decoder network. Specifically, we present a set of grammar rules for converting the LaTeX markup sequence of each expression into a parsing tree; then, we model the markup sequence prediction as a tree traverse process with a deep neural network. In this way, the proposed method can effectively describe the syntax context of expressions, alleviating the structure prediction errors of HMER. Experiments on three benchmark datasets demonstrate that our method achieves better recognition performance than prior arts. To further validate the effectiveness of our method, we create a large-scale dataset consisting of 100k handwritten mathematical expression images acquired from ten thousand writers. The source code, new dataset, and pre-trained models of this work will be publicly available.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Handwritten Mathmatical Expression Recognition | CROHME 2014 | SAN | ExpRate | 56.2 | #11 of 17 | Archive leaderboard | report |
| Handwritten Mathmatical Expression Recognition | CROHME 2016 | SAN | ExpRate | 53.6 | #10 of 16 | Archive leaderboard | report |
| Handwritten Mathmatical Expression Recognition | CROHME 2019 | SAN | ExpRate | 53.5 | #11 of 14 | Archive leaderboard | report |
| Handwritten Mathmatical Expression Recognition | HME100K | SAN | ExpRate | 67.1 | #8 of 12 | 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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