Papers › Towards Unified Scene Text Spotting based on Sequence Generation
Towards Unified Scene Text Spotting based on Sequence Generation
Taeho Kil, Seonghyeon Kim, Sukmin Seo, Yoonsik Kim, Daehee Kim
Sequence generation models have recently made significant progress in unifying various vision tasks. Although some auto-regressive models have demonstrated promising results in end-to-end text spotting, they use specific detection formats while ignoring various text shapes and are limited in the maximum number of text instances that can be detected. To overcome these limitations, we propose a UNIfied scene Text Spotter, called UNITS. Our model unifies various detection formats, including quadrilaterals and polygons, allowing it to detect text in arbitrary shapes. Additionally, we apply starting-point prompting to enable the model to extract texts from an arbitrary starting point, thereby extracting more texts beyond the number of instances it was trained on. Experimental results demonstrate that our method achieves competitive performance compared to state-of-the-art methods. Further analysis shows that UNITS can extract a larger number of texts than it was trained on. We provide the code for our method at https://github.com/clovaai/units.
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Code
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Text Spotting | ICDAR 2015 | UNITS | F-measure (%) - Generic Lexicon | 80.3 | #1 of 18 | Archive leaderboard | report |
| Text Spotting | ICDAR 2015 | UNITS | F-measure (%) - Strong Lexicon | 89.0 | #1 of 18 | Archive leaderboard | report |
| Text Spotting | ICDAR 2015 | UNITS | F-measure (%) - Weak Lexicon | 84.1 | #1 of 18 | Archive leaderboard | report |
| Text Spotting | Total-Text | UNITS | F-measure (%) - Full Lexicon | 86.0 | #5 of 12 | Archive leaderboard | report |
| Text Spotting | Total-Text | UNITS | F-measure (%) - No Lexicon | 78.7 | #5 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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